Journal articles on the topic 'Automated rack supported warehouse'

In the 40 years since 1966, when we completed Japan's first automated warehouse, we have been developing new techniques and products targeting next-generation automated warehouses. Centering on the theme “highly advanced technology,” we have freely used state-of-the-art technology such as drives and software to enhance the applications of stacker cranes and peripheral equipment. Thanks to technological advances, automated warehouses expanded and evolved to provide “sorting and picking” in addition to “storage” advances are expected to bring unprecedented processing speed and high revolution enabling many different and novel distribution systems. Here we introduce the changes that have made the “Rack Master” stacker crane so advanced. The Rack Master is a core component of our automated warehouses.

Efficient path planning for Automated Guided Vehicles (AGVs) in warehouse automation is crucial yet challenging, particularly in environments with irregular structures and constrained spaces. This study addresses these challenges by focusing on AGVs without rotary platforms, which require the rotation of the entire robot-rack assembly for directional changes, demanding additional space and complex path planning. We have developed dedicated algorithms that integrate robotics and optimization principles to tackle these issues. Our methods take into account the spatial requirements for rack rotation, navigating through limited inter-rack clearance, and adapting to irregular warehouse layouts. Extensive simulations and real-world applications validate the proposed solutions, demonstrating significant improvements in traversal efficiency and collision risk mitigation. The results indicate that our algorithms effectively enhance the operational efficiency and reliability of AGV systems in complex warehouse environments. This research adapts AGV path planning by providing robust strategies to optimize navigation in challenging settings, ultimately improving warehouse productivity.

This paper describes the structure composition and characteristic of assembled self-supported warehouse. And its mechanical principle is introduced and compared with both the assembled pallet rack and the building structure. The assembled self-supported warehouse combines the two structure systems effect. The longitudinal horizontal load is transferred to foundation by means of roof truss and multi-pan portal rigid frame and the lateral horizontal load is transferred by means of spine bracing system and semi-rigid frame. Load on roof and goods load are transferred separately from roof truss and beams to columns, then these loads are transferred to foundation.

. В зарубежной практике разработан целый ряд новых технологий и систем для развития складской логистики. Представлены новые реализованные проекты автоматизированных и автоматических складов. Обобщен зарубежный инновационный опыт в складской логистике. Приведены технические показатели высокостеллажных складов и автоматических складов для мелких штучных грузов. Основа инноваций - цифровизация, автоматизация, применение беспилотных транспортных средств и мобильных роботов. In foreign practice, a number of new technologies and systems have been worked out for development of warehouse logistics. New implemented projects of automated and automatic warehouses are discussed. Overseas innovative experience in warehouse logistics is summarized. Technical parameters of high-rack warehouses and automatic warehouses for small-sized piece goods are given. The basis of innovation is digitalization, automation, use of unmanned vehicles and mobile robots.

This paper presents automated storage systems with shuttles integrated with hoisted carriage for successful application in intralogistics. The first part of the paper presents classic and advanced AVS/RS along with specific intralogistics automation systems known as AutoStore from Swisslog and Skypod from Exotec. The second part of the paper focuses on an advanced system with shuttle vehicles capable of serving multiple tiers of the storage rack. An analytical model for the shuttle vehicles capable of serving multiple tiers of the storage rack is presented, which is based on (i) the sequences of acceleration, constant velocity and deceleration, and (ii) randomised assignment policy. Based on the presented model, the expected Single Command (SC) and Dual Command (DC) travel (cycle) time as well as the throughput performance of the shuttle vehicles capable of serving several tiers of warehouse, could be calculated. A programme code in MATLAB has been presented for the computation of throughput performances of automated storage systems with shuttles integrated with hoisted carriage capable of serving several tiers of the storage rack.

This project around “DR digital imaging non-destructive prediction based on automatic warehousing screening technology and application” project can be divided into cable full inspection in coil based on DR digital imaging mode of the whole case study, with a small piece of material screening technology research, based on the data acquisition and recognition algorithm used for the detection of automated storage research and pilot test three corpus. The hardware framework structure and software system security access model are designed based on existing warehouse conditions. A non-destructive batch automatic pre-screening equipment is developed for small materials, which has both DR and CT functions. Cold cathode pulse ray source for needle tip pulse discharge is improved. A set of non-destructive pre-screening equipment for the whole length of the cable is developed and arranged on the warehouse automatic tray wire rack. Through the multiangle scan imaging of two ray sources, the application of image recognition is expanded, and the automatic size labeling problem warning is realized. The non-destructive pre-screening of the whole length of the cable is implemented synchronously during the process of unloading the cable from the warehouse. The insulation layer scars of the wire diameter and thickness are compared and checked, and the quality problems are visually reflected, and the detection report is automatically generated.

The goal of this paper was the design of monitoring system static model for storage and retrieval vehicles in an Automated Warehouse. As usual, the development of a static model required five preliminary steps: analysis of needs, identification of key object, design of static model, define of the attributes for the object class and creation of class diagram. The paper was also presented form above contents. First, the composition and operation process of R/S vehicles monitoring system were analyzed to identify the main entity object (Rack, InOutStation, Crane and association object (ConveyTask). Second, the core model of monitoring system was built up by analyzing the inter-relationships of the main objects. Three, by expanding the core model based on the needs of monitoring system, the static model was gained. Finally, the attributes for the object class were defined and the class diagram was created.

Current pallet design methodology frequently underestimates the load capacity of the pallet by assuming the payload is uniformly distributed and flexible. By considering the effect of payload characteristics and their interactions during pallet design, the structure of the pallets can be optimized, and raw material consumption reduced. The objective of this study was to develop and validate a finite element model capable of simulating the bending of a generic pallet while supporting a payload made of corrugated boxes and stored on a warehouse load beam rack. The model was generalized in order to maximize its applicability in unit load design. Using a two-dimensional, nonlinear, implicit dynamic model, it allowed for the evaluation of the effect of different payload configurations on the pallet bending response. The model accurately predicted the deflection of the pallet segment and the movement of the packages for a unit load segment with three or four columns of boxes supported in a warehouse rack support. Further refinement of the model would be required to predict the behavior of unit loads carrying larger boxes. The model presented provides an efficient solution to the study of the affecting factors to ultimately optimize pallet design. Such a model has not been previously developed. The model successfully acts as a tool to study and predict the load bridging performance of unit loads requiring only widely available input data, therefore providing a general solution.

Industry 4.0 has improved productivity, facilitated work automation and simplified job augmentation. The rising deployment of robotic systems for warehouse automation is primarily responsible for the consistent growth of the Automated Material Handling Systems (AMHS) market. The emergence of Industry 4.0 has facilitated sustainability and ongoing technical breakthroughs. The design and construction of a material-handling prototype robot and monitoring system are described in this work. By reducing the need for humans, this system enables the effective transportation of commodities in the manufacturing area, inventory storage area, and warehouses. Robot mobility is the major emphasis of automated material handling systems, which combine mechanical and electrical components and link hardware and software. The adoption of this system is largely due to the ongoing developments in technologies like the Internet of Things (IoT), which allow for the easy integration of controllers with automated material handling equipment as well as the ability to control machines using a human-machine interface (HMI) by using an application with the additional specification of visualizing the management system by the user, which will retrieve data from the machine using the thing speak platform. Furthermore, continuous automatic staking and unstacking can be achieved in a loop using queuing technology. According to the weight of the materials, using HMI one can select the appropriate slots and place it, which can able to withstand the strain of the rack for a long duration of time.

Automated storage and retrieval systems (AS/RS) play a key role in improving the performance of automated manufacturing systems, warehouses, and distribution centers. In the modern manufacturing industry, the term (AS/RS) refers to various methods under computer control for storing and retrieving loads automatically from defined storage locations. Using an (AS/RS) is not considered a value-added activity. Therefore, the longer (AS/RS) travels, the more expensive the warehousing process becomes. This paper presents an algorithm for minimizing total travel distance/time between input/output (I/O) stations. The proposed algorithm is used to manage the storage and retrieval orders on warehouse shelves in class-based storage on the storage racks. It contains two steps: the first step is to evacuate some storage compartments (locations) near the I/O station; in the second step, some tote bins are reallocated to compartments closer to the I/O station. Among the features of this algorithm are mechanisms that determine the number of reallocated tote bins, which tote bins to reallocate, and in which direction (toward the I/O station or away from it). A simulation model using R software developed specifically for this purpose was used to validate the suggested method. Based on the results, the new method can reduce the service time per order by about 10% to 20%, depending on parameters like the number of orders and the height of the storage rack.

Given the low space usage rate of the traditional automated storage/retrieval system and the long aisle, it is easy for a stacker to take a long time to enter/leave the warehouse. Thus, a new type of double-ended compact storage system is proposed. This paper addresses the scheduling problem for the stacker to execute the single and dual commands mixed tasks in the system where the I/O ports are located at both ends of the aisle, and the power conveyor devices on the rack can meet the requirement of multi-depth storage and generate displacement. An improved shuffled frog leaping algorithm (ISFLA) is developed for the scheduling problem. In order to eliminate the disadvantages of local optimum and slow convergence in the standard shuffled frog leaping algorithm, a set of hybrid perturbation update methods are designed based on a role model learning strategy, and the feasibility of the improved algorithm is verified by a numerical simulation. The experimental results show that the solution quality and the convergence ability of the ISFLA are significantly improved, and it can effectively solve the stacker-scheduling problem in the double-ended compact storage system.

Purpose: Research paper is an extension of the concept connected with demand forecasting function acquisition by logistics operators in the whole distribution network (concept is considered among others in the following papers: (Kmiecik, 2021a, 2021b, 2020). The concept of centralized forecasting assumes that a logistics operator, whose attributes coincide with the features selected through analysis of forecasting-able entities in the distribution networks and flagship enterprises, is able to take over the forecasting function for the whole distribution network. Paper, which is based on the mentioned concept, shows one of the first stages of its implementation. This stage is the implementation of the forecasting tool in the logistics operator's actions to support his operational activities. Currently, the logistics operator doesn't conduct the forecasting activity, but there are attempts aimed at implementation of forecasting tool and increasing the offered services' added value level. Operational activity, which will be first to be supported, is the process of planning the warehouse resources. Mentioned resources concern the human and internal transportation resources, which are needed for fulfilling the processes connected with SKU (Stock Keeping Units) releasing from the warehouse. The main paper purpose to examine the concept the of automated cloud-based resource planning process at the selected 3PL entity which provides logistics services to wide range of manufacturers in the distribution network using the computer simulation model with comparison with the current resource planning process. Design/methodology/approach: Following research paper based on analysis the survey results and analyzing the simulation results. In the survey were tested the warehouse managers which are responsible for resource planning process. The analysis provides the general requirements of managers about resource planning process supported by automated cloud-based demand forecasting solution and information about expected forecasting tool accuracy. In the paper there were also created two simulation models based on BPMN 2.0 standard. First model reflects the current shape of resource planning process and was created to compare to the second, improved model. Improved model includes the examining of automated cloud-based resource planning solution. Findings: The main expectations of 3PL operational managers about usage the demand forecasting tool is to support of warehouse resource planning. They also state that the expected accuracy of such a tool is the weekly MAPE not greater than 5%. The main benefits of proposed solution are the time decreasing, increasing the level of automation, showing the main areas when the agile point of view should be implemented and show the perspective of resource possibility of usage in the different activities (beside the resource planning process). Originality/value: Automation and fully cloud integration will allow to reduce the process time more than 60% (in total and in average one process time). There are also some disadvantages of proposed solution which could be reduced by using other trends connected with Industry 4.0 development and by developing the collaborative strategies of the particular nodes of distribution networks. Keywords: logistics operator; distribution network; warehouse management; demand forecasting; BPMN 2.0 model. Category of the paper: research paper.

The Autonomous Guided Vehicles (AGVs), that relied on tracks and specially defined paths or were to be overseen by operators, AMRs have evolved. PNO AMRs: using a rich set of sensors and artificial intelligence and machine learning, with computation on board for path planning, to interpret and navigate the environment, with no wired power or tethers of any kind. Since AMRs are indeed assemblies of cameras and sensors, if there is a sudden obstacle such as a fallen box or a group of people, the navigation techniques related to collision avoidance should slow down or stop in order to reroute their path across that thing and move forward with the rest of their task. Autonomous mobile robots become increasingly important in modern intralogistics. Automatic or semi-automatic goods transport by driverless platform trucks saves much more noticeably and increases the efficiency of warehouses and logistics hotspots. As they are of low heights, they will pass under rack transporters and trolleys and lift pallets from transfer racks and take them to a defined destination on their own. They perceive and avoid any obstacle to be independently able to reach their destination. Either QR codes attached to the floor or laser-assisted natural feature navigation act as orientation for the AMRs. In contrast, intralogistics is still largely characterized by standard process features, in which goods are transported anyway back to accurate positions along short and medium-length routes. Autonomous mobile robots give significant support to these processes. They relieve workers from monotonous transport tasks and reduce distances for walking, thereby increasing handling capacity and decreasing error and accident rates. They take up no more space than the load to be transported and also maneuverer extremely well in most tight spots, thanks to their compactness and mobility. Integration into established process sequences is especially easy: for example, integration into the warehouse without any problems with other automated components.

In local and globalized markets, warehouses are crucial supply chain nodes. This study aimed to investigate the effect of warehousing on supply chain performance: A case of Inyange Industries Ltd. The goals were to evaluate how inventory management, warehouse capacity building, and material handling affects supply chain performance in Inyange Industries Ltd. This research experimented with three different theories: Just-in-time, Lean, and Triple-A supply chain. The population of this study were 105 staff members of Inyange Industries Ltd. Therefore, census was conducted because the population size is affordable and the researcher can be able to contact all the respondents. Quantitative data were analyzed using inferential research methodology in this study. Questionnaires were used to gather primary data, which was then analyzed. Data analysis was carried out using the Statistical Package for the Social Sciences (SPSS), and descriptive and inferential statistics were used to show the study's results. According to the research, supply chain performance is positively and significantly affected by both automated and manual material handling. Mechanical material handling, on the other hand, improves supply chain performance, but not much. Inyange Industries' supply chain performance is influenced by the material handling systems to the tune of 19.3%, as shown by the modified R2 value of 0.193. According to the research, supply chain performance is positively and significantly affected by inventory counts, warehouse management systems, and inventory organization. A 0.967 adjusted R^2 value suggests that 96.7% of the variation in Inyange Industries' supply chain performance is explained by the inventory management techniques. According to the research, supply chain effectiveness is positively and significantly impacted by warehouse demand planning, design, and management. Warehouse capacity planning techniques at Inyange Industries account for 95.4% of the variation in supply chain performance, as shown by the modified R2 value of 0.954. The research concluded that material handling, inventory management, and warehouse capacity planning are all important warehouse management measures that significantly impact supply chain performance for the better. The methods used by Inyange Industries Ltd. for managing their warehouses have resulted in an improvement in supply chain performance of 87.2%. The regression coefficients, supported by their t-test values and Beta coefficients, highlight both the significance and strength of relationships between independent and dependent variables. Material Handling demonstrated the greatest impact (β1=0.532, t=8.556, p=0.000), followed by Inventory Management (β2=0.379, t=6.147, p=0.000), and Warehouse Capacity Planning (β3=0.172, t=3.268, p=0.002), emphasizing their respective contributions to Supply Chain Performance of Inyange Industries Ltd.'s supply chain. This proved that material handling in warehouse management has a major influence on supply chain performance. Because the p-value was lower than 5%, we may say that the association is statistically significant. The research concluded that both automated and human material handling should get additional funding. To maximize efficiency in stock-taking as well. Previous studies have looked at a variety of organizational factors that affect performance of supply chains. To further understand how warehouse management strategies affect overall performance, more research is needed.

In order to bring intralogistics systems to the same level of interoperability as today’s modern production systems, logistics must take the essential steps towards Industry 4.0. This requires an increasing abstraction level of control logic as an enabler for horizontal and vertical integration. The abstraction will lead to the interconnection ofmanufacturing and logistics control with the production planning and warehouse management systems (WMS). A main enabler for these communication paths are service-oriented architectures (SoA). OPC UA has established itself as a widely used and already adopted SoA-based communication standard in industry. The paper describes the realization of an OPC UAbased approach for the communication between a WMS and a PLC of an automated storage and retrieval system (ASRS). The conceptual basis of communication design are skills of the ASRS. The work is supported by an architectural design with a subsequent prototypical implementation.

ABSTRACT The Adaptive AGV Navigation System is a smart material handling solution designed to automate and optimize operations in small-scale industries. It employs a PIC16F877A microcontroller to control and coordinate various components of the Automated Guided Vehicle (AGV), including DC motors, IR sensors, and RFID-based modular instruction cards. These instruction cards, read by an EM-18 RFID reader, provide real-time task and navigation commands, allowing the AGV to adapt its path dynamically based on operational needs.To ensure accurate control and responsiveness, the system integrates edge computing modules, which locally process sensor data and navigation instructions, significantly reducing latency. The AGV structure is supported by a durable robot chassis, powered by a 5V battery supply, The hardware configuration, supported by modular and reprogrammable components like the motor driver module, allows easy system expansion and reconfiguration without extensive rewiring or infrastructure changes. This makes the solution ideal for flexible production lines, warehouse logistics, and assemblyautomation in small to medium-sized enterprises. By combining intelligent navigation, modular design, and real-time edge processing, this system offers a cost-effective and scalable AGV platform that enhances productivity, reduces manual labor, and supports the transition toward smart industrial automation.

Introduction. The banking sector assigns high priority to data storage, as it is a critical aspect of business operations. The volume of data in this area is steadily growing. With the increasing volume of data that needs to be stored, processed and analyzed, it is critically important to select a suitable data storage solution and develop the required architecture. The presented research is aimed at filling the gap in the existing knowledge of the data base management system (DBMS) suitable for the banking sector, as well as to suggest ways for a fault-tolerant data storage cluster. The purpose of the work is to analyze the key DBMS for analytical queries, determine the priorities of the DBMS for the banking sector, and develop a fault-tolerant data storage cluster. To meet the performance and scalability requirements, a data storage solution with a fault-tolerant architecture that meets the requirements of the banking sector has been proposed.Materials and Methods. Domain analysis allowed us to create a set of characteristics that a DBMS for analytical queries (OnLine Analytical processing — OLAP) should correspond to, compare some popular DBMS OLAP, and offer a fault-tolerant cluster configuration written in xml, supported by the ClickHouse DBMS. Automation was done using Ansible Playbook. It was integrated with the Gitlab version control system and Jinja templates. Thus, rapid deployment of the configuration on all nodes of the cluster was achieved.Results. For OLAP databases, criteria were developed and several popular systems were compared. As a result, a reliable cluster configuration that met the requirements of analytical queries has been proposed for the banking industry. To increase the reliability and scalability of the DBMS, the deployment process was automated. Detailed diagrams of the cluster configuration were also provided.Discussion and Conclusions. The compiled criteria for the DBMS OLAP allowed us to determine the need for this solution in the organization. Comparison of popular DBMS can be used by organizations to minimize costs when selecting a solution. The proposed configuration of the data warehouse cluster for analytical queries in the banking sector will improve the reliability of the DBMS and meet the requirements for subsequent scalability. Automation of cluster deployment by the mechanism of templating configuration files in Ansible Playbook provides configuring a ready-made cluster on new servers in minutes.

Summary Objective: Within translational research projects in the recent years large biobanks have been established, mostly supported by homegrown, proprietary software solutions. No general requirements for biobanking IT infrastructures have been published yet. This paper presents an exemplary biobanking IT architecture, a requirements specification for a biorepository management tool and exemplary illustrations of three major types of requirements. Methods: We have pursued a comprehensive literature review for biobanking IT solutions and established an interdisciplinary expert panel for creating the requirements specification. The exemplary illustrations were derived from a requirements analysis within two university hospitals. Results: The requirements specification comprises a catalog with more than 130 detailed requirements grouped into 3 major categories and 20 subcategories. Special attention is given to multitenancy capabilities in order to support the project-specific definition of varying research and bio-banking contexts, the definition of workflows to track sample processing, sample transportation and sample storage and the automated integration of preanalytic handling and storage robots. Conclusion: IT support for biobanking projects can be based on a federated architectural framework comprising primary data sources for clinical annotations, a pseudonymization service, a clinical data warehouse with a flexible and user-friendly query interface and a biorepository management system. Flexibility and scalability of all such components are vital since large medical facilities such as university hospitals will have to support biobanking for varying monocentric and multicentric research scenarios and multiple medical clients.

Abstract Background Processing data from electronic health records (EHRs) to build research-grade databases is a lengthy and expensive process. Modern arthroplasty practice commonly uses multiple sites of care, including clinics and ambulatory care centers. However, most private data systems prevent obtaining usable insights for clinical practice. Objective This study aims to create an automated natural language processing (NLP) pipeline for extracting clinical concepts from EHRs related to orthopedic outpatient visits, hospitalizations, and surgeries in a multicenter, single-surgeon practice. The pipeline was also used to assess therapies and complications after total hip arthroplasty (THA). Methods EHRs of 1290 patients undergoing primary THA from January 1, 2012 to December 31, 2019 (operated and followed by the same surgeon) were processed using artificial intelligence (AI)–based models (NLP and machine learning). In addition, 3 independent medical reviewers generated a gold standard using 100 randomly selected EHRs. The algorithm processed the entire database from different EHR systems, generating an aggregated clinical data warehouse. An additional manual control arm was used for data quality control. Results The algorithm was as accurate as human reviewers (0.95 vs 0.94; P=.01), achieving a database-wide average F1-score of 0.92 (SD 0.09; range 0.67‐0.99), validating its use as an automated data extraction tool. During the first year after direct anterior THA, 92.1% (1188/1290) of our population had a complication-free recovery. In 7.9% (102/1290) of cases where surgery or recovery was not uneventful, lateral femoral cutaneous nerve sensitivity (47/1290, 3.6%), intraoperative fractures (13/1290, 1%), and hematoma (9/1290, 0.7%) were the most common complications. Conclusions Algorithm evaluation of this dataset accurately represented key clinical information swiftly, compared with human reviewers. This technology may provide substantial value for future surgeon practice and patient counseling. Furthermore, the low early complication rate of direct anterior THA in this surgeon’s hands was supported by the dataset, which included data from all treated patients in a multicenter practice.

The article explores relevant aspects of implementing control in the e-commerce sector within the context of digitalization. It highlights the role of controlling as a tool for making informed managerial decisions, enhancing business process efficiency, reducing costs, and increasing customer satisfaction. The study provides insights into the critical importance of integrating controlling systems with digital technologies to meet the growing demands of the dynamic e-commerce environment. A comprehensive analysis of literary sources and recent scientific research has been conducted to identify key trends in integrating digital technologies into controlling processes. These include automated demand forecasting systems and analytical platforms facilitating real-time data-driven decision-making. Special attention is given to performance metrics such as website conversion rate, average order value (AOV), bounce rate, repeat purchase rate, and metrics related to customer session duration and page views. These indicators are essential for evaluating operational success and identifying improvement areas. The study underscores the significance of automating logistical processes, mainly warehouse management systems (WMS), to streamline the processing of orders and returns. Effective logistics management, supported by controlling, ensures timely delivery, accurate order fulfillment, and cost-efficient returns handling, which are pivotal for sustaining customer trust and loyalty. Furthermore, the article analyzes tools that enable enterprises to respond swiftly to market changes, minimize risks, and improve the quality of managerial decisions. Emphasis is placed on establishing a unified information space to consolidate data from various sources. This remains a critical challenge for advancing controlling practices in e-commerce. Keywords: controlling, e-commerce, digitalization, logistics, returns management, analytics platforms, automation, strategic management.

Customer Relationship Platforms (CRP) are essential tools for managing customer interactions, but traditional systems often fall short in handling the exponential growth of data and the need for real-time insights. This manuscript explores the transformative potential of integrating Artificial Intelligence (AI) into CRP systems, presenting a model for evolving conventional CRP into smart, autonomous solutions. By leveraging AI technologies such as Machine Learning, Natural Language Processing (NLP), and Predictive Analytics, businesses can enhance data processing, automate routine tasks, and deliver personalized customer experiences. The proposed Smart CRP architecture integrates real-time data processing, advanced Data Integration ETL pipelines, scalable data warehousing, automated customer segmentation, predictive modeling, and NLP capabilities. This paper outlines the benefits, challenges, and implementation strategies associated with AI-powered CRP systems, supported by case studies and a detailed architectural model. Future research directions include expanding API integrations, developing advanced AI models, and enhancing transparency and scalability of AI-driven CRP solutions.

Tjangkir Kopi is a small-medium enterprise (MSMEs) engaged in food and beverage in West Java, precisely in City. There is a problem in the current business process, namely in managing the stock of materials that are still done manually through the Microsoft Excel application, which is very likely to occur misunderstandings. Competition in the Food and Beverage Industry is getting tougher, making MSMEs Tjangkir Kopi have to improve their business processes by creating an information system that helps develop their business to achieve a competitive advantage. In addition, there is still a lack of fulfillment of job descriptions for each employee and centralized report data. The System to be Built helps quickly and directly integrate with material stock and expenditure data in the database, so there won't be material stock problems in the warehouse. This system makes transaction reports on business processes much more effective because the data is automated. This research aims to analyze and design systems to support better inventory management and transaction reports and to support business processes with more complete and clear diagrams using the ICONIX Process method. This research explains the stages of analysis by collecting data through interviews and literature studies. The stages of system design produce business process proposals supported by GUI design, use case diagrams, domain models, robustness diagrams, sequence diagrams, and class diagrams. The results of research through analysis and system design using the ICONIX process method, it is hoped that Tjangkir Kopi can use it as an illustration of business processes to develop the business to be better and able to compete with competitors.

e14062 Background: Real world evidence generated from electronic health records (EHRs) is playing an increasing role in health care decisions. It has been recognized as an essential element to assess cancer outcomes in real-world settings. Automatically abstracting outcomes from notes is becoming a fundamental challenge in medical informatics. In this study, we aim to develop a system to automatically abstract outcomes (Progression, Response, Stable Disease) from notes in lung cancer. Methods: A lung cancer cohort (n = 5,003) was obtained from the Mount Sinai Data Warehouse. The progress, pathology and radiology notes of patients were used. We integrated various techniques of Natural Language Processing (NLP) and Artificial Intelligence (AI) and developed a system to automatically abstract outcomes. The corresponding images, biopsies and lines of treatments (LOTs) were abstracted as attributes of outcomes. This system includes four information models: 1. Customized NLP annotator model: preprocessor, section detector, sentence splitter, named entity recognition, relation detector; CRF and LSTM methods were applied to recognize entities and relations. 2. Clinical Outcome container model: biopsy evidence extractor, lines of treatment detector, image evidence extractor, clinical outcome event recognizer, date detector, and temporal reasoning; Domain-specific rules were crafted to automatically infer outcomes. 3. Document Summarizer; 4. Longitudinal Outcome Summarizer. Results: To evaluate the outcomes abstracted, we curated a subset (n = 792) from patient cohort for which LOTs were available. About 61% of the outcomes identified were supported by radiologic images (time window = ±14 days) or biopsy pathology results (time window = ±100 days). In 91% (720/792) of patients, Progression was abstracted within a time window of 90 days prior to first-line treatment. Also, 72% of the Progression events identified were accompanied by a downstream event (e.g., treatment change or death). We randomly selected 250 outcomes for manual curation, and 197 outcomes were assessed to be correct (precision = 79%). Moreover, our automated abstraction system improved human abstractor efficiency to curate outcomes, reducing curation time per patient by 90%. Conclusions: We have demonstrated the feasibility and effectiveness of NLP and AI approaches to abstract outcomes from lung cancer EHR data. It promises to automatically abstract outcomes and other clinical entities from notes across all cancers.

In order to reduce costs for a larger warehouse or expand the floor space of a small warehouse, it is impossible to implement this with a traditional warehouse, which is characterized as poorly utilized space. For the efficient storage and retrieval, the smart warehouse system with autonomous mobile-rack vehicles can optimize the space utilization by providing only a few open aisles at a time for accessing the racks with minimal intervention. This paper deals with designing the vehicle robust controller for maintaining safe spacing with collision avoidance in the fully automated warehouse. The compact vehicle dynamics are presented for the interconnected string of vehicles. Next, the string stability with safe working space of the mobile-rack vehicles has been described for guaranteeing complete autonomous logistics in smart warehouse. In addition, the controller order has been significantly reduced to a low-order system without performance degradation for real implementation. This control method can guarantee control stability as well as performances of mobile-rack vehicles against unavoidable uncertainties, disturbances, and noises for warehouse automation in the extremely cold environment without rail rack. Finally, the autonomous mobile-rack vehicle system is to become the promising vision of future smart warehouse technology in autonomous logistics.

AbstractSteel racking systems are widely adopted for storage purposes: they are thin-walled structures composed of consecutive trusses, connected with beams on which the palletized goods are stored. Their geometry and structural configuration strongly depend on market and operator necessities, and, in modern applications, racks can also function as the supporting structure of the warehouse itself in the form of Rack Supported or High-Bay Warehouses. With the increase of the overall geometric dimensions and the global weight of the stored material, the seismic action becomes more relevant for the design. Along these lines, the development and experimental testing of a dedicated seismic design approach for ductile steel racks is here presented, with particular attention to Rack Supported Warehouses. This approach exploits the ductility of trusses introduced via the plastic ovalization mechanism of the diagonal-to-upright connections while a tailored capacity design is used to assure the elastic behaviour of the rest of the structure and to keep the brittle failure mechanisms at bay.

ObjectivesPublic health service organisations use multiple patient administration and electronic health record systems. We describe the implementation of a data warehouse automation tool within the National Centre for Healthy Ageing (NCHA) data platform to operationalise a research data warehouse to optimise data quality and data provision for health services research.
 ApproachThe traditional data warehouse life cycle comprises repetitive manual tasks and dependency on specialist developers. Automation tools overcome most of these inefficiencies. We conducted an internal risk benefit analysis which was validated by published literature containing data warehouse optimisation and automation. Industry-based data warehouse automation tools were reviewed to align the NCHA requirements with the tool’s functionality. Tools were then shortlisted and evaluated over a six-week period: (1) automation of standard tasks; (2) data pipeline alignment with the World Health Organization’s (WHO) Data Quality Review Framework; and (3) resource dependency risk mitigation through a Proof of Concept (PoC).
 ResultsThe priority areas identified by the risk benefit analysis included: end-to-end data warehouse automation; auto scripting; connectivity/linkage with multiple sources, reverse/forward engineering, audit trail conformance, scalability, multiple data warehouse architectures support, automated documentation; data management including data quality; and post-subscription independence. Twenty scientific publications were included in the final literature review (10% within healthcare) and supported the majority of identified priority areas. The industry-based review identified 11 suitable data warehouse/Extract-Transform-Load (ETL) automation tools. Five tools demonstrated adequate performance for task automation, data quality management, reduced dependency on specialist developers and on-premise linkage compatibility. Two automation tools were tested each for 6 weeks through PoC development. One automation tool met 8 out of the 10 automation requirements and was selected for implementation.
 ConclusionData warehouse development processes are complex and time consuming. Tools that offer automation of repetitive tasks and scripting increase the consistency while reducing the dependency on specialist staff. Integrated data quality management minimises the time researchers spend in pre-processing patient level data sourced through a semi-automated data warehouse.

Current trends in manufacturing are characterized by production broadening, innovation cycle shortening, and the products having a new shape, material and functions. The production strategy focused on time needed change from the traditional functional production structure to flexible manufacturing cells and lines. Production by automated manufacturing system (AMS) is one of the most important manufacturing philosophies in the last years. The main goals of the project we are involved in lies on building a laboratory in which will be located a flexible manufacturing system consisting of at least two production machines with NC control (milling machines, lathe). These machines will be linked to a transport system and they will be served by industrial robots. Within this flexible manufacturing system a station for the quality control consisting of a camera system and rack warehouse will be also located. The design, analysis and improvement of this manufacturing system, specially with a special focus on the communication among devices constitute the main aims of this paper. The key determining factors for the manufacturing system design are: the product, the production volume, the used machines, the disposable manpower, the disposable infrastructure and the legislative frame for the specific cases.

Multi-tote storage and retrieval (MTSR) autonomous mobile robots can carry multiple product totes, store and retrieve them from different shelf rack tiers, and transport them to a workstation where the products are picked to fulfill customer orders. In each robot trip, totes retrieved during the previous trip must be stored. This leads to a mixed storage and retrieval route. We analyze this mixed storage and retrieval route problem and derive the optimal travel route for a multiblock warehouse by a layered graph algorithm, based on storage first-retrieval second and mixed storage and retrieval policies. We also propose an effective heuristic routing policy, the closest retrieval (CR) sequence policy, based on a local shortest path. Numerical results show that the CR policy leads to shorter travel times than the well-known S-shape policy, whereas the gap with the optimal mixed storage and retrieval policy in practical scenarios is small. Based on the CR policy, we model the stochastic behavior of the system using a semiopen queuing network (SOQN). This model can accurately estimate average tote throughput time and system throughput capacity as a function of the number of robots in the system. We use the SOQN and corresponding closed queuing network models to optimize the total annual cost as a function of the warehouse shape, the number of robots, and tote buffer positions on the robots for a given average tote throughput time and throughput capacity. Compared with robots that retrieve a single tote per trip, an MTSR system with at least five buffer positions can achieve lower operational costs while meeting given average tote throughput time and tote throughput capacity constraints. Funding: This work was supported by National Natural Science Foundation of China [Grant 72372088] and the Shenzhen Science and Technology Program [Grant GJHZ20220913143003006]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0397 .

<em>Electronic Customer Relationship Management(E-CRM) is one of business concepts and technology that supported by information systems to integrate all of business proccess that customer interacted. The most common implementation of E-CRM in warehouse systems is a website. This study is to know the role of E-CRM to improve the quality of services, describe the implementation of E-CRM, understand the warehousing procedure, and know the quality of services through E-CRM in AT Multimodal Logistics. E-CRM is a strategy that integrates the concepts of knowledge management, data mining and data warehousing to support an organization&#39;s decision-making process in order to maintain long-term and profitable relationships with its customers. AT Multimodal Logistics E-CRM is applied in conjunction with general information, alternative contact, membership, automated email, and new customer instructions. </em>

Many online retailers apply scattered (or mixed-shelves) storage in the picking areas of their warehouses. Instead of keeping unit loads together, individual pieces of stock keeping units (SKUs) are stored on various shelves throughout the warehouse. This storage strategy increases the probability that—whatever it is that customers order jointly—somewhere in the warehouse these products will be located in close proximity. Hence, a picker can retrieve them without excessive unproductive walking. The price for this advantage on the picking side, however, is additional effort for the replenishment workers (also denoted as stowers) when restocking the shelves. Instead of moving only a single homogeneous unit load toward an SKU’s designated storage position, each stower has to travel along multiple open shelf spaces until all products on the cart are stored on shelves. The resulting stower routing problem is equivalent to the well-known prize collecting traveling salesman problem (PCTSP). While the PCTSP for general graphs is known to be strongly [Formula: see text]-hard, we show that in a warehousing environment, where all open storage positions are located along parallel aisles, it is only binary [Formula: see text]-hard. The special parallel-aisle structure allows us to derive an exact solution algorithm with pseudo-polynomial runtime, which solves even instances with hundreds of open storage positions to proven optimality in just a few seconds. Our computational tests show that the performance gains of an optimized stowing process over the status quo, where stowers operate without decision support, are significant. Especially, when the fill level of a warehouse is high, directing stowers on optimized routes promises huge improvements. History: Accepted by Andrea Lodi, Area Editor for Design &amp; Analysis of Algorithms – Discrete. Funding: This work was supported by the German Science Foundation/Deutsche Forschungsgemeinschaft (DFG) by the grant “Routing of human and automated order pickers in modern warehouses” (BO 3148/14-1 and BO 1972/2-1). Supplemental Material: The e-companion is available at https://doi.org/10.1287/ijoc.2022.0173 .

Authors: Susanne de Witt, Frauke Swieringa, Judith Cosemans &amp; Johan Heemskerk ### Abstract Thrombus formation by adhering and aggregating blood platelets is fundamental to hemostasis and is a prerequisite for vascular occlusion in pathological thrombosis. The parallel-plate flow chamber technique has been extensively used to measure platelet adhesion and activation in vitro at arterial or venous flow conditions. Here, we describe the use of brightfield and confocal fluorescence microscopy to record the various platelet activation processes contributing to thrombus formation on microspotted arrays of thrombogenic surfaces; and we give procedures to analyze the acquired microscopic images. Furthermore, we describe technical problems that can be expected using the microspot technique. Content: (A) Flow chamber preparation and whole blood perfusion. (B) Brightfield and fluorescence microscopic imaging of thrombi. (C) Analysis of brightfield and fluorescence images. ### Introduction Thrombus formation by adhering and aggregating blood platelets is fundamental to hemostasis and is a prerequisite for vascular occlusion in pathological thrombosis. The parallel-plate flow chamber technique has been extensively used to measure platelet adhesion and activation in vitro at arterial or venous flow conditions. However, current tests use collagen as the only platelet-adhesive surface, thereby disregarding the contribution of other platelet-adhesive components in the vascular matrix. This is a relevant issue, since multiple platelet adhesive receptors need to interact and signal to form a stable platelet thrombus. On type I collagen fibers, the two collagen receptors, glycoprotein VI (GPVI) and integrin α2β1 (GPIa/IIa) interact with the receptors for von Willebrand factor (vWF), a plasma protein that avidly binds to collagen, i.e. GPIb-V-IX and integrin αIIbβ3 (GPIIb/IIIa).(6-8) It is hence relevant to compare the roles of these receptors with other ones, such as CLEC-2, CD36 (GPIV), and the integrins α5β1, α6β1 and αvβ3. In the accompanying paper, we have described a microspot technology, in which various platelet-adhesive compounds can be coated simultaneously in a flow chamber, and directly compared for their potential to support thrombus formation using small blood samples.(9) When forming a thrombus, platelets show different types of responses, all of which may contribute to effective hemostasis and pathological thrombosis. These include shape change (pseudopod and lamellipod formation), integrin activation, secretion of the contents of dense granules and α-granules (P-selectin exposure), and actin-dependent contraction of the formed thrombus.(1,5) In addition, a subpopulation of the platelets – with high cytosolic Ca2+ – assumes a balloon-type of morphology and exposes the procoagulant phospholipid phosphatidylserine (PS) at their outer surface, at which coagulation factors bind and thrombin can be formed.(10) Since it is unclear how these different platelet responses relate during thrombus formation, we developed procedures to measure these in a systematic way in combination with the microspot technology.(9) In this protocol paper, we describe the use of brightfield and confocal fluorescence microscopy to record the various platelet activation processes contributing to thrombus formation; and we give procedures to analyze the acquired microscopic images. We note that all assays are performed in the absence of coagulation. Furthermore, we stress that: due to space restrictions not all details could be given; specific procedures may need adaptation in different laboratories; and that expert knowledge will be required for successful completion of the flow assays. We welcome comments on errors and suggestions for improvement. Content: - A. Flow chamber preparation and whole blood perfusion. - B. Brightfield and fluorescence microscopic imaging of thrombi. - C. Analysis of brightfield and fluorescence images. ### Materials Reagents 1. Annexin A5 labeled with Alexa Fluor (AF)647 (Molecular Probes, A23204) - Bovine serum albumin (BSA) (Sigma Aldrich, A6003) - CaCl2 (Sigma Aldrich, C1016) - 3,3’ Dihexyloxacarbocyanine iodide (DiOC6) (Anaspec, 8984715) - Ethanol (VWR) - FITC-labeled anti-CD62P (P-selectin) mAb (Immunotech, A07790) - Fragmin (Pfizer, 5T1532) - D-Glucose (ACS Reagent) - HCl (Sigma Aldrich, H1758) - 4-(2-Hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES) (Sigma Aldrich, H3375) - KCl (Sigma Aldrich, P9541) - MgCl2 (Sigma Aldrich, M8266) - D-Phenylalanyl-L-prolyl-L-arginine chloromethylketone (PPACK) (BioConnect, A58SC-201291A) - NaCl (Sigma Aldrich) - Unfractionated heparin (Sigma Aldrich, H3393-1) - FITC-labeled anti-fibrinogen mAb (WAK Chemie Medical, 64162) Solutions 1. Blocking buffer: 136 mM NaCl, 10 mM HEPES, 2.7 mM KCl, 2 mM MgCl2, 1% BSA in milliQ water (pH 7.45). - Coverslip cleaning solution: 2 M HCl in 50% ethanol. - DiOC6 in 1% DMSO in buffer - Flow buffer: 136 mM NaCl, 10 mM HEPES, 2.7 mM KCl, 2 mM MgCl2, 2 mM CaCl2, 0.1% glucose, 0.1% BSA, 1 U/mL heparin in milliQ water (pH 7.45). - Platelet-adhesive substances for coating are described elsewhere.9 For coating collagen peptides, also see previous papers.11,12 Note that collagens and collagen solutions require storage in acid milieu.8,12 - PPACK in 10 mM HCl - Saline: 0.9% NaCl in milliQ water (sterilized). ### Equipment 1. Glass coverslips (24×60 mm, thickness 0.18 mm) (Menzel BB024060A1) - Precision mall with template for one or two rows of three microspots (3 mm centre-to-centre distance) for placement on glass coverslip. Note: apply either 1×3 or 2×3 microspots, depending on the possibility to observe these by the microscope. - Humid chamber for storing coated coverslips. - Open parallel-plate flow chamber: transparent polycarbonate block with engraved flow channel (50 μm depth, 3 mm width, 30 cm length, inlet/outlet tubes at an angle of 11°). The Maastricht chamber has been described before. It needs to be fixed in an aluminium holder with screws.4 - Silicon tubing (0.28 mm ID, 0.61 mm OD; Rubber BV Hilversum). - Blunt syringe needles (18 gauge) to connect with tubing. - Surgical tweezers to clamp tubing. - Pulse-free syringe perfusion pump Type 100 (Harvard Instruments). - Needle or system for blood drawing (e.g., 23 gauge). - Plastic syringes 1 mL (Becton-Dickinson). - 5 mL polystyrene tube (Greiner Bio-One). ### Procedure **Procedures A. Flow chamber preparation and whole blood perfusion** **A1. Preparation of coverslips** *CRITICAL. Wash cleaned coverslips thoroughly with water*. - 1.Degrease new coverslips (use tweezers) with 2 M HCl in 50% ethanol. - 2.Wash coverslips twice with milliQ water to remove residual HCl. - 3.Leave coverslips to dry on drying rack. **A2. Coating of coverslips** *CRITICAL. Prevent drying of biological material on coverslip by storing in humid environment*. - 4.Prepare coating material (collagen, collagen peptide, decorin, fibrinogen, fibronectin, laminin, osteopontin, rhodocytin, thrombospondin, vitronectin, vWF), at 50-250 μg/mL, as described.(9) - 5.Mount coverslip onto precision mall for coating. - 6.Apply 0.5 µL of coating solution(s) in the assigned place(s), and remove from the mall. - 7.Store coverslip in humid environment to prevent drying out of microspots. Allow coating material to bind for 60 minutes at room temperature. - 8.Block uncoated glass with blocking buffer, and leave in humid environment for 30 minutes. - 9.Wash blocked coverslip with saline. If not immediately used, leave coverslip in humid environment to prevent drying. **A3. Assembly of coverslip and flow chamber** *CRITICAL. Check for leakage of the mounted flow chamber. Also check rigorously for absence of air bubbles before starting the experiment. Note that temperature changes can lead to appearance of air bubbles. Keep inlet tubing as short as possible* - 10.Connect tubing to inlet and outlet of the flow chamber. - 11.Rinse chamber and tubing with flow buffer, check for absence of air bubbles, and mount coated coverslip on top of chamber. - 12.Place chamber with coverslip in aluminium holder and tighten screws. - 13.Check that flow chamber system is leak-tight by perfusion with flow buffer, flush out any bubbles in chamber. **A4. Drawing of human blood by venipuncture** *CRITICAL: Before drawing human blood, obtain permission from your Medical Ethical Committee, according to the local and national regulations, and get full informed consent from donor. Coagulation (traces of thrombin) need to be rigorously prevented by drawing without constraints, mixing well with anticoagulant, and incubation at 37oC. Note that PPACK is only shortly active as an anticoagulant at neutral pH. Other possible errors are described elsewhere.(4)* - 14.Add 0.5 mL saline into a 5 mL polystyrene blood collection tube. Add 40 U/mL (f.c.) fragmin, and add 40 µM PPACK (f.c.) just before venipuncture. - 15.Draw blood according to local protocols, and let smoothly flow into collection tube. Directly mix blood with anticoagulant solution. We prefer an open system using a 23 gauge needle, to ensure undisturbed flow. Discard first 1 mL of blood before filling blood collection tube. - 16.Incubate the collected blood at 37°C for 10-15 minutes to allow platelets to resensitize. - 17.Preferably, determine platelet and red cell counts. A decrease in platelet count points to aggregation of platelets, e.g. by traces of thrombin. - 18.Add additional 20 µM PPACK (f.c.) once per hour. **A5. Blood perfusion through flow chamber** *CRITICAL: Check for correct pump settings to obtain the requested shear rate. Check for absence of air bubbles and fibrin clots during the experiment. Preferably use an inverted microscope. Several possible errors are described elsewhere.(4)* - 19.Only for experiments to determine stable platelet adhesion or thrombus volume, add 0.5 µg/mL DiOC6 (f.c.) to 0.5 mL blood sample. Allow staining of the blood cells for 5 minutes. - 20.Draw 0.5 mL blood sample into 1 mL syringe equipped with blunt needle. Make sure that no air is present in top of needle. - 21.Connect syringe with blood sample to inlet tubing of prepared flow chamber. Carefully avoid air bubbles (fluid-fluid contact). - 22.Prepare 1 mL syringe with flow buffer with required fluorescent labels. The following labels are suitable for post-staining: FITC-labeled anti-CD62P mAb (1.25 µg/mL) or FITC-labeled anti-fibrinogen mAb (1:100) and/or AF647-labeled annexin A5 (0.25 µg/mL) (all f.c.). - 23.Mount flow chamber and holder on stage of the microscope, and identify position of microspots with camera. Focus on optical plane of one microspot. - 24.Place syringe filled with whole blood on perfusion pump (push mode). Ensure proper pump settings (arterial wall shear rate: 1600 s^-1 for 3.5 minutes or 1000 s^-1 for 4 minutes; venous wall shear rate 150 s^-1 for 6 minutes). Note that the wall shear rate depends on the flow rate and the dimensions of the flow chamber. For calculation, see elsewhere.(4) - 25.Switch pump on. The experiment starts when the blood has reached the site of the microspots. **A6. Recording of stable adhesion and thrombus volume using DiOC6-labeled platelets** *CRITICAL: Rinse shortly to prevent disaggregation of thrombi*. - 26.During the first 2 minutes of whole blood perfusion, record DiOC6 fluorescence microscopic images at 2-seconds intervals (real-time recording of stable platelet adhesion). - 27.After 3.5, 4 or 6 minutes of perfusion (depending on shear rate), change syringe with blood by syringe with flow buffer; set pump rate at 1000 s^-1. - 28.For 2 minutes, rinse chamber with flow buffer. - 29.Take confocal z-stacks from thrombi during stasis; 2 to 3 stacks per microspot (recording of thrombus volume). **A7. Recording of brightfield images and post-staining with fluorescent labels** *CRITICAL: Rinse shortly to prevent disaggregation of thrombi. Prevent air bubbles in flow chamber during syringe replacements*. - 30.Starting from point 25. - 31.At the end of the whole-blood perfusion, change syringe with blood by syringe with fluorescent labels; set pump rate at 1000 s-1. - 32.For 2 minutes, perfuse buffer with labels through flow chamber; leave 1 minute for staining. - 33.During the perfusion, take brightfield microscopic images (5 per microspot) under flow. - 34.Change syringe with labels by syringe with flow buffer; and perfuse for 2 minutes to remove unbound label. - 35.Take fluorescence images during stasis (5 images per microspot). **Procedures B. Brightfield and fluorescence microscopic imaging of thrombi** **B1. Use of LSM 7 LIVE line-scanning confocal fluorescence microscope** *SPECIFICATION: Recording of stable platelet adhesion and thrombus volume (DiOC6-labeled platelets). Use in confocal mode for rapid real-time scanning of platelet adhesion, and of z-stacks to determine thrombus volume (see also Ref.12). Collect only sharp, high-quality images! Three color staining is possible (excitations 485, 530, 640 nm)*. - 1.Microscope: inverted confocal fluorescence microscope: Axio Observer Z1 (Carl Zeiss) with differential interference contrast (DIC) optics. Camera: AxioCam HRm (Zeiss). Scanning stage with insert for flow chamber holder. - 2.Laser head: LSM 7 Live (Zeiss). Lasers: DOPP 488 nm (100 mW), DPSS 532 nm (75 mW), Laser 635 nm (30 mW). - 3.Objective: 63x oil immersion (Zeiss, PlanApo, NA 1.40; DIC M27, WD 0.19 mm). - 4.Settings: [configuration 488 laser line] - a.Excitation 488 nm, emission filter 495-555 nm, pinhole 1 AU. - b.For time series: 1 cycle of 2 minutes with 2-seconds interval, laser power 5%, gain 5, zoom 0.5x, scan speed 3-4 Lps. - c.For z-stack: 0.5 µm between optical planes (70 slices), laser power 5%, gain 5, zoom 1x, scan speed 1 Lps. - 5.Controlling software: ZEN 2010 (Zeiss). - 6.Output images: LSM file (512×512 pixels, 107×107 µm or 213×213 µm (depending on zoom), 8-bit). **B2. Use of BioRad/Zeiss Radiance 2100 laser scanning confocal microscope** *SPECIFICATION: Imaging of thrombi post-labeled with FITC (OG488) and AF647 probes. Flow chamber with labeled thrombi is placed on stage up-side down. Scan with large pin holes to collect fluorescence from all optical planes. Collect only sharp, high-quality images! Three color staining is possible (excitations 485, 530, 640 nm)*. - 7.Microscope: right-up fluorescence microscope E600FN (Nikon, Japan). Scanning stage with insert for flow chamber holder. - 8.Laser head: BioRad/Zeiss scan head. Lasers: Argon 488 nm (40 mW), Green He/Ne 543 nm (1.5 mW), Red diode 638 nm (5 mW). - 9.Objective: 60x oil immersion (Nikon, PlanApo SFluor, NA 1.30, WD 0.22 mm). - 10.Settings: Two-color fluorescence: - a.PMT1: excitation 488 nm, laser power 20%, iris 1.5, emission filter 508-523 nm - b.PMT2: excitation 637 nm, laser power 50%, iris 3.5, emission filter &gt;660 nm - c.zoom 1, Kalman averaging 2, scan speed 160 Lps. - 11.Recording software: LaserSharp 2000 software (Zeiss). - 12.Output images: PIC file (512×512 pixels, 200×200 µm, 8-bit). **B3. Use of camera-based non-confocal fluorescence microscope system** *SPECIFICATION: Imaging of thrombi post-labeled with FITC (OG488) and AF647 probes. Furthermore, recording of brightfield phase-contrast images to determine platelet deposition. Collect only sharp, high-quality images!* - 13.Microscope: inverted fluorescence microscope Diaphot 200 (Nikon) with phase-contrast. Two cameras connected with beam splitter, post-magnification and removable infrared filter. Vista brightfield CCD camera; Hamamatsu EM-CCD C9100-12 fluorescence camera. Scanning stage with insert for flow chamber holder. - 14.Fluorescence: Xenon lamp (100 W). Filter cube: FITC (OG488): exciter 485 ± 11 nm, dichroic 400 nm, emitter 530 ± 15 nm. Brightfield trans-illumination (white light). - 15.Objective: 40x oil-immersion (Nikon, Fluor/100, NA 1.30. Ph4DL, WD 0.20 mm). - 16.Settings: - a.Brightfield phase-contrast (empty filter cube). Post-magnification: 1x - b.Fluorescence: excitation 485 nm, emission 530 nm. Post-magnification: 1.5x. - 17.Recording software: Axiovision 4.8 (Zeiss). - 18.Output images: TIFF file (512×512 pixels, 200×200 µm, 8-12 bit). **B4. Use of EVOS table fluorescence microscope** *SPECIFICATION: Imaging of thrombi post-labeled with FITC (OG488) and AF647 probes. Furthermore, recording of brightfield images to determine platelet deposition (overlays can be made). Collect only sharp, high-quality images! Three color staining is possible (excitations 485, 530, 640 nm)*. - 19.Microscope: EVOS-FL, inverted microscope, infinity-corrected fluorescence optical system. - 20.LED diodes: DAPI 357 nm (emission 447 nm), GFP 470 nm (emission 510 nm), RFP 531 nm (emission 593 nm), Cy5 626 nm (emission 692 nm). Brightfield trans-illumination (white light). - 21.Objective: 60x oil immersion (Olympus, UPlanSApo, NA 1.35, WD 0.15 mm). - 22.Settings: adjustable intensity of LEDs - a.Brightfield: transmitted light at intensity of 50%. - b.GFP cube: excitation 470 nm, emission 510 nm, intensity 40%. - c.Cy5 cube: excitation 626 nm, emission 692 nm, intensity 20%. - 23.Recording software: integrated in EVOS system. Make sure to save images of individual colors. - 24.Output images: TIFF file (1360×1024 pixels, 142×107 µm, 8-bit). **Procedures C. Analysis of brightfield and fluorescence images** **C1. Image analysis for morphological score** *CRITICAL: Analysis of images blinded for the experimental condition*. - 1.Determine morphological score of thrombi on coverslip based on recorded brightfield phase-contrast or DIC images. - 2.Score at a 5-point scale (see Fig. 1). **C2. Image analysis with package Metamorph (Molecular Devices)** *CRITICAL: Measurement of surface area coverage of brightfield and fluorescence images. The following procedures apply to 8-bit TIFF and PIC images. Conversion to 8-bit images can be done using ImageJ software (Open access). Image analysis can also be performed with ImageJ. Output data are given as numbers of pixels per region. To determine surface area coverage, use total pixel number of images. Note that the outcome of the analyses depends on the quality of the recorded images*. - **1.Protocol for stable platelet adhesion (see Fig. 2)** - a.Threshold every image within one time series with the same threshold → binary image. - b.In “process” and “arithmic”, choose the first binary image as “source image 1” and the second binary image as “source image 2”. - c.Click “subtract” with constant values at “0”. - d.Choose apply. - e.Repeat steps a-d for the next images. - f.Choose “measure” → “integrated morphometry analysis”. Measure all binary images and subtracted images. - g.Export all values to Excel spreadsheet, and calculate % of change between consecutive images. - **2.Protocol for surface area coverage of aggregated platelets (see Fig. 3A)** - a.For each image, use edge detection in both horizontal (150) and vertical (150) direction. - b.Use the horizontally filtered image for threshold setting → binary image. - c.Use morphological close filter (diamond, width = 12) and open filter (circle, diameter = 5). - d.Transfer regions to brightfield/fluorescence image, and check if region detection is right. - e.Export data to Excel file, and convert pixel numbers to % surface-area-coverage. - **3.Protocol for surface area coverage of platelet monolayers (see Fig. 3B)** - a.Filter images using morphological bottom hat filter (diamond, width = 15), then close filter (diamond, width = 4). - b.Threshold closed image  binary image. - c.Apply morphological dilate filter (square, width = 2). - d.Transfer regions to original image, and check if region detection is right. - e.Export data to Excel file, and convert pixel numbers to % surface-area-coverage. - **4.Protocol for integrated feature size** - a.The integrated feature size (IFS) is a value taking into account the proportional contribution of large and small thrombi on microspots. It represents the cumulative contribution of squared features, ranked from small to large individual features, with (f) from small to large are numbered 1-N. For formula see Ref. 9. - b.First, from an analyzed image, rank the individual features (pixels per region) from small to large (one image = one column with features) in an Excel file. - c.Determine the pixel size of one single platelet. Exclude all features smaller than this size (≈ 100 pixels). - d.Integrate the values of the features (accumulated sum of pixels). - e.Convert pixel size into µm2. - f. Divide the accumulated feature size by the accumulated sum of all feature sizes, and express as percentage. - g.Calculate the area above the percentage curve in µm2. - h.Express results on a logarithmic scale. **C3. Image analysis with package Axiovision 4.8 (Zeiss) for thrombus volume** *CRITICAL: This program uses LSM files, and allows writing of scripts for automated image analysis. Common output is: ID region, volume unscaled (pixel3), surface (µm2) and volume (µm3) per region. Summative data can be calculated per region.* - 1.Use scrap filter with minArea: 1 and maxArea: 100 (see Fig. 3C). - 2.Use separation filter with count: 3 and in Morphology mode. - 3.Transfer regions to original image, and check if region detection is right. - 4.Export data to Excel file, and convert pixel numbers to µm3. ### References 1. Swieringa F, Kuijpers MJ, Heemskerk JW and van der Meijden PE (2014) Targeting platelet receptor function in thrombus formation: the risk of bleeding. *Blood Rev*. 28:9-21. - Roest M, Reininger A, Zwaginga JJ, King MR and Heemskerk JW (2011) Flow chamber-based assays to measure thrombus formation in vitro: requirements for standardization. *J. Thromb. Haemost*. 9:2322-23224. - Cosemans JM, Mattheij NJ, Angelillo-Scherrer A and Heemskerk JW (2013) The effects of arterial flow on platelet activation, thrombus growth and stabilization. *Cardiovasc. Res*. 99:342-352. - Van Kruchten R, Cosemans JM and Heemskerk JW (2012) Measurement of whole blood thrombus formation using parallel-plate flow chambers: a practical guide. *Platelets* 23:229-242. - Versteeg HH, Heemskerk JW, Levi M and Reitsma PS (2013) New fundamentals in hemostasis. *Physiol. Rev*. 93:327-358. - Ruggeri ZM and Mendolicchio GL (2007) Adhesion mechanisms in platelet function. *Circ. Res*. 100:1673-1685. - Siljander PR, Munnix IC, Smethurst PA, Deckmyn H, Lindhout T, Ouwehand WH, Farndale RW and Heemskerk JW (2004) Platelet receptor interplay regulates collagen-induced thrombus formation in flowing human blood. *Blood* 103:1333-1341. - Heemskerk JW, Sakariassen KS, Zwaginga JJ, Brass LF, Jackson SP, Farndale (2011) Collagen surfaces to measure thrombus formation under flow: possibilities for standardization. *J. Thromb. Haemost*. 9:856-858. - De Witt SM, Swieringa F, Cavill R, Lamers MM, van Kruchten R, Mastenbroek T, Baaten C, Coort S, Pugh N, Schulz A, Scharrer I, Jurk K, Zieger B, Clemetson KJ, Farndale RW, Heemskerk JW and Cosemans JM (2014) Identification of platelet function defects by multi-parameter assessment of thrombus formation. *Nat. Commun*. 5:4257, 2014. DOI: 10.1038/ncomms5257 - Heemskerk JW, Mattheij N and Cosemans JM (2013) Platelet-based coagulation: different populations, different functions. *J. Thromb. Haemost*. 11:2-11. - Munnix IC, Gilio K, Siljander PR, Raynal N, Hackeng T, Feijge MA, Deckmyn H, Farndale RW and Heemskerk JW (2008) Affinity modulation of triple-helical peptides for binding to integrin 21 and glycoprotein VI affects thrombus formation under flow: a study with collagen-mimicking peptides. *J. Thromb. Haemost*. 7:2132-2142. - Pugh N, Simpson AM, Smethurst PA, de Groot PG, Raynal N and Farndale RW (2010) Synergism between platelet collagen receptors defined using receptor-specific collagen-mimetic peptide substrata in flowing blood. *Blood* 115:5069-5079. - Pugh N, Bihan D, Perry DJ and Farndale RW (2014) Dynamic analysis of platelet deposition to resolve platelet adhesion receptor activity in whole blood at arterial shear rate. Platelets, in press. ### Acknowledgements This work was supported by grants from the Center for Translational Molecular Medicine (INCOAG), the Dutch Heart Foundation (2011T6), the Landsteiner Foundation for Blood Transfusion Research (1006) and ZonMW (MKMD 114021004). We thank R. Verdoold and L. Baaten for help with figure preparations. ### Figures **Figures 1-3: Assessment of morphological score and the processing of images for multi-parameter analysis**  **Fig. 1**. Assessment of morphological score of thrombi on 0-5 point scale. Representative images are given with description of scores  **Fig. 2**. Intermediate processed images for determination of stable platelet adhesion, as described in the protocol. Time is in seconds  **Fig. 3**. Results of automated image analysis, as described in the protocols. Sequences to determine surface area coverage of aggregated platelets (A) and of platelet monolayers (B), starting from phase-contrast images. Sequence to determine thrombus volume from stacks of fluorescence images (C). ### Associated Publications This protocol is related to the following articles: **Identification of platelet function defects by multi-parameter assessment of thrombus formation**, Susanne M. de Witt, Frauke Swieringa, Rachel Cavill, Moniek M.E. Lamers, Roger van Kruchten, Tom Mastenbroek, Constance Baaten, Susan Coort, Nicholas Pugh, Ansgar Schulz, Inge Scharrer, Kerstin Jurk, Barbara Zieger, Kenneth J. Clemetson, Richard W. Farndale, Johan W.M. Heemskerk, and Judith M.E.M. Cosemans, Nature Communications 5, 16/07/2014 *Source: [Protocol Exchange](http://www.nature.com/protocolexchange/protocols/3309). Originally published online 26 August 2014.*