Journal articles: 'Manufacturing processes. Production planning. Production scheduling'

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Sugimura, Nobuhiro, Koji Iwamura, and Tomohiko Maeda. "Special Issue on Production Planning and Scheduling." International Journal of Automation Technology 9, no. 3 (May 5, 2015): 209. http://dx.doi.org/10.20965/ijat.2015.p0209.

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This issue focuses on production planning and scheduling for production system and the related problems that have arisen in these areas in the last half century as digital computer systems developed. These problems relate to production management, production planning, shop floor control, product design and process planning. In the first stage of production planning and scheduling systems R&D, optimization is a key issue that has been widely discussed and many theories and optimization algorithms proposed. Rule-based methods are discussed as potential solutions to these problems. With rapid advances in computer and information processing technologies and performance, tremendous progress has been made in the areas of production systems such as production planning, production scheduling, advances production systems (APS), enterprise resource planning (ERP), just-in time (JIT) processes, the theory of constraint (TOC), product data management (PDM) and computer-aided design / manufacturing / engineering (CAD/CAM/CAE). This special issue addresses the latest research advances, applications, and case studies in production planning and scheduling covering such as decentralized and autonomous production systems, distributed simulation models, robust capacity planning models, wireless sensor networks for production systems and applications to automotive component and steel production. We hope that learning about these advances will enable readers to share their own experience and knowledge in technology, new developments and the potential applications of production planning and scheduling methods and solutions.

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HE, YAN, FEI LIU, and JINLIANG SHI. "A FRAMEWORK OF SCHEDULING MODELS IN MACHINING WORKSHOP FOR GREEN MANUFACTURING." Journal of Advanced Manufacturing Systems 07, no. 02 (December 2008): 319–22. http://dx.doi.org/10.1142/s0219686708001413.

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Reducing environmental impacts and resource consumption in manufacturing processes is one of the important issues in green manufacturing. However, this attention has focused primarily on the activities of the design and the process planning, and the production scheduling activity has been overlooked especially for discrete manufacturing systems such as machining workshop. This paper presents a framework of the scheduling models in machining workshop that integrated resource and environmental considerations into production scheduling activities. The scheduling framework builds upon the schematic model and the analysis of resource and environmental dimensions of machining processes, and is used to guide the scheduling model construction which seeks to reduce resource consumption and environmental impacts at the operational scheduling level. The example is presented to demonstrate the application of the framework.

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Kolus, Ahmet, Ahmed El-Khalifa, Umar M. Al-Turki, and Salih Osman Duffuaa. "An integrated mathematical model for production scheduling and preventive maintenance planning." International Journal of Quality & Reliability Management 37, no. 6/7 (April 21, 2020): 925–37. http://dx.doi.org/10.1108/ijqrm-10-2019-0335.

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PurposeThe integration between production scheduling and maintenance planning is attracting the attention of planners in the manufacturing sector with the increase in global competitiveness. Researchers have developed various methodologies to optimize integrated decisions in planning and scheduling, including mathematical modeling under different conditions. This paper considers the simultaneous scheduling of production and maintenance activities with the objective of minimizing the expected total tardiness cost on a single machine (production line).Design/methodology/approachScheduling in these two types of activities, production and maintenance, are traditionally done independently, causing conflicts between the two functional areas. To eliminate or at least reduce conflicts, the scheduling of both activities can be done simultaneously with the objective of meeting due dates and maintaining maximum machine availability. In this paper, a mathematical model for an integrated problem is developed and demonstrated by an example.FindingsThe proposed integrated model shows a high potential for significant improvements in performance with respect to the cost of tardiness in delivery and machine availability. This is demonstrated by an example showing an average savings of approximately 40%.Originality/valueThis substantial saving is owed to the integration of two important decision-making processes in manufacturing systems. Although the integrated problem is complex and difficult to solve, the fact that it is savings driven makes the problem of interest to researchers and practitioners in manufacturing.

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Younus, Muhammad, Yong Yu, Hu Lu, and Yu Qing Fan. "Study and Execution of Advanced Batch Production Planning System for an Aerospace Industry." Applied Mechanics and Materials 16-19 (October 2009): 748–52. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.748.

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Modern manufacturing industries are increasingly faced with international competition and fluctuating market conditions in the age of globalization. In striving to remain competitive, manufacturing industries must deliver products to customer at the lowest cost, at the best quality and in the minimum lead time. As a result, it becomes mandatory to design and implement the advance production planning and scheduling system that supports shorter product cycles despite more complex and specialized manufacturing processes. The advance production planning and scheduling system provides the leaner production strategies and real time information throughout the industry. This paper presents an appropriate Advance Production Planning and Scheduling Software System for a batch production aerospace manufacturing industry. The Software system receive the customer‘s order and perform material requirement planning using software. The software system sends procurement requisition to the procurement department for the materials which is not available in the store for manufacturing of parts. It issues release order to the store section for the issuance of material to the manufacturing shops. It also issues weekly and daily plan with production schedule to the manufacturing shops. It also issues work orders to the production shops for the manufacturing and assembly of the parts. On the completion of the product assembly, proper closing of the work orders has to be done and product may deliver to the warehouse for further handing over to the customers. In case of modification of order by the customer, the Software System will automatically update the relevant data.

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Tanizaki, Takashi, Hideki Katagiri, and António Oliveira Nzinga René. "Scheduling Algorithms Using Metaheuristics for Production Processes with Crane Interference." International Journal of Automation Technology 12, no. 3 (May 1, 2018): 297–307. http://dx.doi.org/10.20965/ijat.2018.p0297.

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This paper proposes scheduling algorithms using metaheuristics for production processes in which cranes can interfere with each other. There are many production processes that involve cranes in manufacturing industry, such as in the steel industry, so a general purpose algorithm for this problem can be of practical use. The scheduling problem for this process is very complicated and difficult to solve because the cranes must avoid interfering with each other plus each machine has its own operational constraints. Although several algorithms have been proposed for a specific problem or small-scale problem, general purpose algorithms that can be solved in real time (about 30 minutes or less) in the company’s production planning work have not been developed for large-scale problems. This paper develops some metaheuristic algorithms to obtain suboptimal solutions in a short time, and it confirms their effectiveness through computer experiments.

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Kalinowski, Krzysztof, Cezary Grabowik, Grzegorz Ćwikła, and Witold Janik. "The Graph of Operations Planning Sequence of a Production Order for Scheduling with Mixed Planning Strategies and Alternatives." Applied Mechanics and Materials 809-810 (November 2015): 1420–25. http://dx.doi.org/10.4028/www.scientific.net/amm.809-810.1420.

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The paper presents the most important issues related to the scheduling of production orders in real manufacturing systems. In the elaborated method an and/or type graph of operations planning sequence of a production order is proposed for modelling the production system load. In a single structure the graph takes into account alternative routes of a production order realisation and the precedence constraints in presence of complex, hierarchical structures of processes. Two modelling ways of that process using the "operation on the edge" or "operation on the node" notation are also presented. In the developed method scheduling strategies, which have a major impact on the order of placing operations in the schedule and handling of production lots are also considered. By a state space graph representation of scheduling problem, using graph theory, it can be possible to analyze the structure and complexity of both the modelling problem and the graph search techniques.

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Bin, Zeng, and Jing Zhang. "Design of a Resource Scheduling Tool for Production Project Management." Applied Mechanics and Materials 220-223 (November 2012): 165–68. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.165.

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Production planning is clearly needed in all manufacturing systems, and that is also the case for job shops. When dealing with a small number of products or jobs repetitive scheduling becomes a major issue. In this situation, the same tasks are performed sequentially and repeated from job to job. To help with this problem, a resource scheduling tool is developed that would work alongside Microsoft Project. This tool should act as a front end to Microsoft Project and allow for the creation of a schedule with a minimal amount of work for the scheduling manager. Due to the repetitive nature of production processes, the tool should be able to eliminate most of the manual scheduling currently done exclusively in MS Project.

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Alvandi, Samira, Wen Li, and Sami Kara. "An Integrated Simulation Optimisation Decision Support Tool for Multi-Product Production Systems." Modern Applied Science 11, no. 6 (April 23, 2017): 56. http://dx.doi.org/10.5539/mas.v11n6p56.

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Over the past decades, the rising energy prices and imposing environmental regulations have motivated manufacturers to improve the energy efficiency of their manufacturing processes. Manufacturers need to also consider energy efficiency in addition to classical performance measures. The additional performance dimension (energy-related indicators) significantly increases the complexity of classical production planning problems (e.g. scheduling), already known as NP-hard problem).To overcome the inherited complexity, an integrated simulation-optimization framework is proposed. The proposed approach tackles scheduling problem in a multi-product/multi-machine manufacturing environment and optimizes several production objectives simultaneously. A case study is presented to demonstrate the applicability of the proposed approach in a real-life industrial facility.

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Yang, Zhixin, Wei Xu, Pak-Kin Wong, and Xianbo Wang. "Modeling of RFID-Enabled Real-Time Manufacturing Execution System in Mixed-Model Assembly Lines." Mathematical Problems in Engineering 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/575402.

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To quickly respond to the diverse product demands, mixed-model assembly lines are well adopted in discrete manufacturing industries. Besides the complexity in material distribution, mixed-model assembly involves a variety of components, different process plans and fast production changes, which greatly increase the difficulty for agile production management. Aiming at breaking through the bottlenecks in existing production management, a novel RFID-enabled manufacturing execution system (MES), which is featured with real-time and wireless information interaction capability, is proposed to identify various manufacturing objects including WIPs, tools, and operators, etc., and to trace their movements throughout the production processes. However, being subject to the constraints in terms of safety stock, machine assignment, setup, and scheduling requirements, the optimization of RFID-enabled MES model for production planning and scheduling issues is a NP-hard problem. A new heuristical generalized Lagrangian decomposition approach has been proposed for model optimization, which decomposes the model into three subproblems: computation of optimal configuration of RFID senor networks, optimization of production planning subjected to machine setup cost and safety stock constraints, and optimization of scheduling for minimized overtime. RFID signal processing methods that could solve unreliable, redundant, and missing tag events are also described in detail. The model validity is discussed through algorithm analysis and verified through numerical simulation. The proposed design scheme has important reference value for the applications of RFID in multiple manufacturing fields, and also lays a vital research foundation to leverage digital and networked manufacturing system towards intelligence.

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Ba, Li, Yan Li, Mingshun Yang, Xueliang Wu, Yong Liu, Xinqin Gao, and Zhihong Miao. "A Mathematical Model for Multiworkshop IPPS Problem in Batch Production." Mathematical Problems in Engineering 2018 (2018): 1–16. http://dx.doi.org/10.1155/2018/7948693.

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Integrated Process Planning and Scheduling (IPPS) problem is an important issue in production scheduling. Actually, there exit many factors affecting scheduling results. Many types of workpieces are commonly manufactured in batch production. Moreover, due to differences among process methods, all processes of a workpiece may not be performed in the same workshop or even in the same factory. For making IPPS problem more in line with practical manufacturing, this paper addresses an IPPS problem with batches and limited vehicles (BV-IPPS). An equal batch splitting strategy is adopted. A model for BV-IPPS problem is established. Makespan is the objective to be minimized. For solving the complex problem, a particle swarm optimization (PSO) with a multilayer encoding structure is proposed. Each module of the algorithm is designed. Finally, case studies have been conducted to validate the model and algorithm.

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Stambolov, Grigor, and Petya Petkova. "Conception of Scheduling and Planning in Reconfigurable Work Stations on the Base of IEC 61499 Function Blocks." Applied Mechanics and Materials 621 (August 2014): 167–80. http://dx.doi.org/10.4028/www.scientific.net/amm.621.167.

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One of the latest solutions in automated production systems is developing of Reconfigurable Manufacturing Systems (RMSs), which have an open structure that allows the integration of new technologies and modifying manufacturing for a new type of production based on adding, removing or updating the elements and units in the hardware and software level. To realize the automated processing RMS needs to have decentralized architecture, including hardware (module based) and software reconfiguration, which to enable distributed control, monitoring and diagnostics in real time and dynamic planning processes and resources in the system. One of the ways to realize this architecture is to development RMS control system on the base of IEC 61499 function blocks (FBs). Important part of the control system is a module for distributed planning and scheduling of processes, which consists all available information for technology of the products. This paper presents an approach for development of scheduling and planning modules in reconfiguration cutting work station on the base of IEC 61499 function blocks.

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Kareem, B., and HA Owolabi. "Optimizing Maintenance Planning in the Production Industry Using the Markovian Approach." Journal of Engineering Research [TJER] 9, no. 2 (December 1, 2012): 46. http://dx.doi.org/10.24200/tjer.vol9iss2pp46-63.

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Maintenance is an essential activity in every manufacturing establishment, as manufacturing effectiveness counts on the functionality of production equipment and machinery in terms of their productivity and operational life. Maintenance cost minimization can be achieved by adopting an appropriate maintenance planning policy. This paper applies the Markovian approach to maintenance planning decision, thereby generating optimal maintenance policy from the identified alternatives over a specified period of time. Markov chains, transition matrices, decision processes, and dynamic programming models were formulated for the decision problem related to maintenance operations of a cable production company. Preventive and corrective maintenance data based on workloads and costs, were collected from the company and utilized in this study. The result showed variability in the choice of optimal maintenance policy that was adopted in the case study. Post optimality analysis of the process buttressed the claim. The proposed approach is promising for solving the maintenance scheduling decision problems of the company.

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Kalinowski, Krzysztof, and Iwona Paprocka. "Scheduling Schemes Based on Searching the Aggregated Graph of Operations Planning Sequence." Applied Mechanics and Materials 809-810 (November 2015): 1462–67. http://dx.doi.org/10.4028/www.scientific.net/amm.809-810.1462.

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The searching state space in scheduling of real manufacturing systems with discrete and multi-assortment production is discussed in this paper. The production load is represented by a directed and/or graph called “the aggregated graph of operations planning of the set of orders”. It determines the order of operations, according to which they will be inserted into a schedule. This order must always comply with all assumed precedence and resource constraints and also with given scheduling strategy of a production order. In the elaborated representation the complex products structures and alternative routes of their realization are also considered. The most important issues related to searching this space are discussed in this paper. These include: a general method for searching the graph, sequencing of parallel processes and operations using schedule generation schemes and selection of routes variants.

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Kang, Hyoung Seok, Sang Do Noh, Ji Yeon Son, Hyun Kim, Jun Hee Park, and Ju Yeon Lee. "The FaaS system using additive manufacturing for personalized production." Rapid Prototyping Journal 24, no. 9 (November 12, 2018): 1486–99. http://dx.doi.org/10.1108/rpj-11-2016-0195.

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PurposeIn this paper, a three-dimensional (3D) printer-based manufacturing line and supporting system, which supports personalized/customized manufacturing for individual businesses or start-up companies, was studied to evaluate the practicality of using additive manufacturing for personalization/mass customization.Design/methodology/approachFirst, factory-as-a-service (FaaS) system, which provides factory as a service to customers, was proposed and designed to manufacture various products within a distributed manufacturing environment. This system includes 3D printer-based material extrusion processes, vapor machine/computer numerical control machines as post-processes and assembly and inspection processes with an automated material handling robot in the factory. Second, a virtualization module for the FaaS factory was developed using a simulation model interfaced with a cloud-based order and production-planning system and an internet-of-things-based control and monitoring system. This is part of the system for manufacturing operations, which is capable of dynamic scheduling in a distributed manufacturing environment. In addition, simulation-based virtual production was conducted to verify and evaluate the FaaS factory for the target production scenario. Main information of the simulation also has been identified and included in the virtualization module. Finally, the established system was applied in a sample production scenario to evaluate its practicality and efficiency.FindingsAdditive manufacturing is a reliable, feasible and applicable technology, and it can be a core element in smart manufacturing and the realization of personalization/mass customization.Originality/valueVarious studies on additive manufacturing have been conducted with regard to replacing the existing manufacturing methods or integrating with them, but these studies mostly focused on materials or types of additive manufacturing, with few advanced or applied studies on the establishment of a new manufacturing environment for personalization/mass customization.

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Zhang, Hua, Gang Zhao, Zhi Gang Jiang, Yan Hong Wang, and Ming Xiao. "Integrated Technology Based on Resource and Environment Attributes for Workshop Planning and Production Operation." Advanced Materials Research 255-260 (May 2011): 2914–18. http://dx.doi.org/10.4028/www.scientific.net/amr.255-260.2914.

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In this paper, the integrated technology based on resource and environment attributes is presented for the workshop planning and production operation. Applying this integrated technology, a demonstration workshop of thermoelectrical valve manufacturer has been constructed to meet the demands of enterprise development. On a principle of green planning, the workshop structure and partition function, the devices layout and the scheduling mode aiming at the minimum energy consumption and noise yield are rebuilt on the base of the present manufacturing process and devices in a representative manufacturer. In this research work, the actual production data of the manufacturer is gathered, arranged, formatted and quantified to build a resource and environment attribute database for the conventional manufacturing process. The key of the integrated technology is to model the full life cycle production for the typical products in the workshop. Via the attribute analysis of the resource consumptions and environment impacts, some adaptive processes of green manufacturing and several prototypes of process device are offered for the respective process of the real production in the workshop. The integrated technology for the workshop planning and production operation is entirely realized and an environmental benefit is gained remarkably.

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Fidlerová, Helena, Jan Prachař, and Peter Sakál. "Application of Material Requirements Planning as Method for Enhancement of Production Logistics in Industrial Company." Applied Mechanics and Materials 474 (January 2014): 49–54. http://dx.doi.org/10.4028/www.scientific.net/amm.474.49.

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Material requirements planning (MRP) is a production planning and inventory management system used to manage logistics processes and designed to assist production managers in scheduling and placing orders for items of dependent demand. If it is implemented and used properly, it can be helpful for production managers to plan capacity needs and allocate production time. The article provides characteristics of the mentioned method; it describes the possible areas of application in manufacturing, purchasing and delivering activities. The paper considers the analysis of the production logistics in the chosen industrial company, focusing on information MRP system and the bottlenecks in the production. The work is a part of KEGA project No. 037STU-4/2012 Implementation of the subject Entrepreneurship Corporate Social Responsibility into the study program Industrial management in the second degree at the MTF STU Trnava.

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Costantino, Francesco, Giulio Di Gravio, and Massimo Tronci. "Integrating Environmental Assessment of Failure Modes in Maintenance Planning of Production Systems." Applied Mechanics and Materials 295-298 (February 2013): 651–60. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.651.

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Apart from preventing and controlling economical, technical and safety impacts of failures, so to reduce at best production losses, maintenance target is to systematically check and improve the allocation and usage of resources in order to assure quality of products and processes. At the same time, consumption of resources and their relative environmental impacts are becoming a central issue in the new international regulations and standards for sustainable manufacturing. On these considerations, the paper proposes an innovative methodology that, starting from the principles of FMECA (Failure Mode, Effects and Criticality Analysis), extends its own concepts with the introduction of a specific index to measure environmental effects of failures. Starting from the traditional definition of the RPN (Risk Priority Number) of a failure mode, the approach defines a new indicator (Environmental Indicator) to extend the results of FMECA and take in consideration the most critical issues of environmental protection: consumption of materials, emissions and wastes, lifespan of systems. Using this tool, maintenance scheduling can be defined considering also an environmental perspective. The methodology is tested on the maintenance program of a manufacturing line in a pharmaceutical production system and results are compared to the one obtained using a traditional FMECA approach.

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Shim, Sang-Oh, KyungBae Park, and SungYong Choi. "Sustainable Production Scheduling in Open Innovation Perspective under the Fourth Industrial Revolution." Journal of Open Innovation: Technology, Market, and Complexity 4, no. 4 (September 21, 2018): 42. http://dx.doi.org/10.3390/joitmc4040042.

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This research addresses a specific issue in the field of operation scheduling. Even though there are lots of researches on the field of planning and scheduling, a specific scheduling problem is introduced here. We focus on the operation scheduling requirements that the Fourth Industrial Revolution has brought currently. From the point of view of open innovation, operation scheduling is known as the one that is using the Internet of Things, Cloud Computing, Big Data, and Mobile technology. To build proper operation systems under the Fourth Industrial Revolution, it is very essential to devise effective and efficient scheduling methodology to improve product quality, customer delivery, manufacturing flexibility, cost saving, and market competence. A scheduling problem on designated parallel equipments, where some equipments are grouped according to the recipe of lots, is considered. This implies that a lot associated with a specific recipe is preferred to be processed on an equipment among predetermined (designated) ones regardless of parallel ones. A setup operation occurs between different recipes of lots. In order to minimize completion time of the last lot, a scheduling algorithm is proposed. We conducted a simulation study with randomly generated problems, and the proposed algorithm has shown desirable and better performance that can be applied in real-time scheduling.

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Tu, Ying-Mei. "Short-Term Scheduling Model of Cluster Tool in Wafer Fabrication." Mathematics 9, no. 9 (May 1, 2021): 1029. http://dx.doi.org/10.3390/math9091029.

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Since last decade, the cluster tool has been mainstream in modern semiconductor manufacturing factories. In general, the cluster tool occupies 60% to 70% of production machines for advanced technology factories. The most characteristic feature of this kind of equipment is to integrate the relevant processes into one single machine to reduce wafer transportation time and prevent wafer contaminations as well. Nevertheless, cluster tools also increase the difficulty of production planning significantly, particularly for shop floor control due to complicated machine configurations. The main objective of this study is to propose a short-term scheduling model. The noteworthy goal of scheduling is to maximize the throughput within time constraints. There are two modules included in this scheduling model—arrival time estimation and short-term scheduling. The concept of the dynamic cycle time of the product’s step is applied to estimate the arrival time of the work in process (WIP) in front of machine. Furthermore, in order to avoid violating the time constraint of the WIP, an algorithm to calculate the latest time of the WIP to process on the machine is developed. Based on the latest process time of the WIP and the combination efficiency table, the production schedule of the cluster tools can be re-arranged to fulfill the production goal. The scheduling process will be renewed every three hours to make sure of the effectiveness and good performance of the schedule.

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Matondang, Abdul Rahim, and Widodo Widodo. "PERENCANAAN DAN PENGENDALIAN KAPASITAS PRODUKSI PRODUK RAKITAN RADIO TIPE SOUNESS SNI 4250." Jurnal Sistem Teknik Industri 20, no. 1 (August 18, 2018): 40–47. http://dx.doi.org/10.32734/jsti.v20i1.383.

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Production system take an important role in industries, especially in manufacturing industries. This role determine the keys of successful company. Production process is an activity which produce finished product from raw material that involve machine, energy, and technique knowledge. Production process is real activity and can be seen by human being. The problems those always be faced in indutries management’s are the arrangement of production schedule, such lack of inventory or overstock once the settlement of production process isn’t on time. Production planning and control is activity to determine what product that will be produced, how many product that will be produced and how many labors needed in production processes. By using production planning and control’s method, those problems can be minimalized. Aggregate planning is one of production planning a.nd control’s method. By using this method, production planning could be done by using unit of replacement product so that the output of this planning isn’t declared in individual product. So, the output of aggregate planning isn’t planning in form of individual product but aggregate’s product. There are some strategies on aggregate planning such as pure strategy on aggregate planning and mixed strategy on aggregate planning. In this research, method of aggregate planning that used is optimization approach by linier rule. This method used to make long term planning and middle term planning. Long term planning consists of product forecasting and aggregate planning. The middle term planning consist of master production schedule and rough cut capacity planning. The result of this research is capacity needed and capacity available to determine which work center is drum and which isn’t. Conclusion of this research that capacity of each work center in perioad january to december 2018 is non drum. This indicate the good scheduling in capacity planning.

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Yamada, Tuane Tonani, Marcelo Seido Nagano, and Hugo Hissashi Miyata. "Minimization of total tardiness in no-wait flowshop production systems with preventive maintenance." International Journal of Industrial Engineering Computations 12, no. 4 (2021): 415–26. http://dx.doi.org/10.5267/j.ijiec.2021.5.002.

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Efficient business organizations must balance quality, cost, and time constraints in competitive environments. Reflecting the complexity of this task, we consider manufacturing systems including several stages of production chains requiring time measurement. When production scheduling is not prioritized in such enterprises, several negative effects may occur. A corporation may suffer financial penalties as well as negative brand exposure, and thus may find its credibility challenged. Therefore, in this study, we propose constructive methods to minimize a total tardiness criterion, considering preventative maintenance constraints to reflect the reality of industrial practice, focusing on a no-wait flowshop environment in which jobs are successively processed without operational interruptions. In addition to proposing constructive methods to solve the no-wait flowshop production scheduling problem, a metaheuristic is presented as an approach to improve results obtained by constructive methods. Computational experiments were designed and performed to compare several production scheduling algorithms. Among various constructive heuristics considered, an algorithm called HENLL using an insertion logic showed the best performance. The proposed metaheuristic is based on the iterated greedy (IG) search method, and the results obtained demonstrated significant improvement compared to the heuristics alone. It is expected that this study may be used by production planning and control (PPC) professionals to apply the proposed method to schedule production more efficiently. We show that the proposed method successfully presented a better solution in relation to total tardiness, considering the above mentioned environment.

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Jin, Liangliang, Chaoyong Zhang, Xinyu Shao, and Xudong Yang. "A study on the impact of periodic and event-driven rescheduling on a manufacturing system: An integrated process planning and scheduling case." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 231, no. 3 (August 6, 2016): 490–504. http://dx.doi.org/10.1177/0954405416629585.

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The integration of process planning and scheduling is a very important problem because it proposes a new idea for improving the performance of a manufacturing system. At present, most existing studies on this problem are static, which assumes that all the jobs to be processed are available in the beginning. However, the practical processing situation is dynamic, such as new job arrivals. Since dynamic production situations are different with static cases, it is important to study the characteristics of actual production situations. In this article, the characteristics of dynamic integrated process planning and scheduling problem with job arrivals are studied. A novel mixed integer linear programming model is established to accommodate new job arrivals, and three criteria (makespan, stability, and tardiness) are considered. New periodic and event-driven rescheduling strategies are presented. In the proposed strategy, newly added jobs together with uncompleted jobs will be rescheduled by non-dominated sorting genetic algorithm-II to obtain the optimal Pareto front when the rescheduling procedure is triggered. The entropy-based weight assigning method together with the Technique for Order of Preference by Similarity to Ideal Solution method is adopted to determine an appropriate schedule among the resultant non-dominated solutions. A set of well-known benchmark instances is employed to investigate the characteristics of the dynamic integrated process planning and scheduling problem with random job arrivals. Experimental results show that the length of a scheduling interval, the number of newly added jobs, and the shop utilization have an important influence on the efficiency of a manufacturing system.

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Sharma, R., and Kim Tae-wan. "Development of a Logic-Based Product Life-Cycle Management (LBPLM) System for Shipbuilding Industry—Conceptual Development." Journal of Ship Production and Design 26, no. 04 (November 1, 2010): 231–51. http://dx.doi.org/10.5957/jspd.2010.26.4.231.

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Product life-cycle management (PLM) has become something like "a magic wand" for various industries because of its capability to integrate different product modules via online network through the product's complete life cycle and hence to provide one-window access, thereby making the whole processes of product conception, design, manufacturing, delivery, maintenance, and disposal integrated with a reduction in product development time and cost. However, heavy industries (i.e., shipbuilding and shipbreaking) are different from consumer product industries because of high customization in design process and engineering software, widely varying scales of operations, and less compatibility between different design and production processes, for example, ship production is planned in activity-driven network scheduling system, in general, and is assumed to be more of a construction process or assembly process rather than a production process. In this paper, we present the conceptual development and the basic building concepts for a logic-based PLM system for the shipbuilding industry. Our logic bases consist of modularization, standardization, geographical zoning, and functional zoning. The logic bases of modularization and standardization are used in the ship design and production processes, and the logic bases of geographical zoning and functional zoning are used in "logically grouping" the on-board activities in the ship production process. Overall, this paper introduces a logic-driven methodology for PLM: planning and integration of ship design and production processes. Finally, in our implementation we show that by developing a logic-based PLM system the ship design and production processes become more streamlined and better planned and executed.

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Shi, Xiao Qiang, Li Jiang Huang, and Hui Wang. "A Multi-Agent System for Remanufacturing of End-of-Life Products." Advanced Materials Research 655-657 (January 2013): 2025–32. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.2025.

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Efficient remanufacturing of end-of-life (EOL) products is crucial for environment friendly production. Disassembly is part of the remanufacturing and it is meant to obtain components and materials from end-of-life products. An essential performance objective of a disassembly process is the benefits it brings, that is the revenue brought by the retrieved parts and material, diminished by the cost of their retrieval operations. A decision must be taken to balance the disassembly production system. In this paper, a multi-agent system (MAS) is presented to optimize the remanufacturing process of EOL products. The MAS offers a synthesized information platform for various tasks, e.g. product/manufacturing information processing, disassembly sequencing, solution performance assessing, and processes scheduling. On one hand, the MAS could retrieve much information related design/manufacturing resources, by multi-level data obtaining mechanism. On the other hand, this information will make the prospective integrated environment for profitable remanufacturing system planning more feasible.

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Коновалова, Галина, and Galina Konovalova. "SYSTEM APPROACH BASED INVESTIGATION OF PRODUCTION AND ENGINEERING COMPANY MANAGEMENT." Bulletin of Bryansk state technical university 2016, no. 4 (December 28, 2016): 295–303. http://dx.doi.org/10.12737/23267.

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Today at engineering companies there is the fol-lowing problem: the inconsistency in management decision-making causing high production costs, a longer duration of a production cycle and a nonobservance of timing of orders. To solve this problem the author of this paper has analyzed with system positions produc-tion and management at an engineering company. A system model is offered, there is described an enlarged structure, hierarchy and kinds of ends, a functional model of engineering company management is formed. In the functional model there are presented functions of a company, production and information flows. In the management scheme of a company there are formulated strategies, ends and indices of efficiency in the field of investigations and developments, finances, marketing, production. A production strategy, budget and orders connect the scheme of company management and the scheme of production management. In the scheme of production management there is located a development of processes for decision-making support, scheduling, online planning, production control, material procurement, resources control, servicing management, company shipments. The scheme of production management has two levels: a company level and a workshop one. Functions of online production planning at a company level provide the formation of a production program, plan-schedules of manufacturing products, parts, units, material requirements, manhours, production costs. Functions of on-line production planning at the workshop level ensure the formation of production schedule and working up urgent plan tasks for production sections (brigades). The influence of external and internal factors upon management system formation is described. The technical solutions offered are introduced at the closed company of “UK “Bryansk Engineering Plant” and have a universal character and may be used at all engineering companies of the country.

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Yin, Peng-Yeng, Hsin-Min Chen, Yi-Lung Cheng, Ying-Chieh Wei, Ya-Lin Huang, and Rong-Fuh Day. "Minimizing the Makespan in Flowshop Scheduling for Sustainable Rubber Circular Manufacturing." Sustainability 13, no. 5 (February 28, 2021): 2576. http://dx.doi.org/10.3390/su13052576.

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It is estimated that 1 billion waste tires are generated every year across the globe, yet only 10% are being processed, and much rubber waste is yielded during manufacturing. These waste tires and rubber scraps are poisonous to the environment when processed via incineration and landfill. Rubber circular manufacturing is an effective solution that reduces not only rubber waste but also raw material costs. In this paper we propose a two-line flowshop model for the circular rubber manufacturing problem (CRMP), where the job sequence of two production lines is appropriately aligned to obtain the shortest makespan while guaranteeing that sufficient rubber waste yielded in the first line is ready to be reused for circular production in the second line. A genetic algorithm (GA) is developed, and the design of its genetic operations is customized to the CRMP context to achieve efficient and effective evolution. The experimental results with both real and synthetic datasets show that the GA significantly surpasses two heuristics in the literature by delivering the minimum makespan, which is 3.4 to 11.2% shorter than those obtained by the two competing methods.

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Göppert, Amon, Leon Mohring, and Robert H. Schmitt. "Predicting performance indicators with ANNs for AI-based online scheduling in dynamically interconnected assembly systems." Production Engineering 15, no. 5 (May 8, 2021): 619–33. http://dx.doi.org/10.1007/s11740-021-01057-z.

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AbstractMass customization demands shorter manufacturing system response times due to frequent product changes. This increase in system dynamics imposes additional flexibility requirements especially on assembly processes, as complexity accumulates in this last step of value creation. Flexible and dynamically interconnected assembly systems can meet the increased requirements as opposed to traditional dedicated assembly line approaches. The high complexity and dynamical environment in these kinds of systems lead to the demand for real-time online control and scheduling solutions. Within the decision-making of online scheduling, the capability of predicting the consequences of available actions is crucial. In real-time environments, running extensive discrete-event simulations to evaluate how actions unfold requires too much computing time. Artificial neural networks (ANN) are a viable alternative to quickly evaluate the potential future performance value of a production state for online production planning and control. They can predict performance indicators such as the expected makespan given the current production status. Leveraging recent advances in artificial intelligence (AI) game algorithms, an assembly control system based on Google DeepMind’s AlphaZero was created. Specifically, an ANN is incorporated into the approach that suggests favorable job routing decisions and predicts the value of actions. The results show that the trained network can predict favorable actions with an accuracy of over 95% and estimate the makespan with an error smaller than 3%.

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Shi, W., D. B. Tang, and P. Zou. "Multi-objective automated guided vehicle scheduling based on MapReduce framework." Advances in Production Engineering & Management 16, no. 1 (March 26, 2021): 37–46. http://dx.doi.org/10.14743/apem2021.1.383.

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During material handling processes, automated guided vehicles (AGVs) pose a path conflict problem. To solve this problem, we proposed a multi-objective scheduling model based on total driving distance and waiting time, and used the A* path planning algorithm to search the shortest path of AGV. By using a speed control strategy, we were able to detect the overlap path and the conflict time. Additionally, we adopted an efficient MapReduce framework to improve the speed control strategy execution efficiency. At last, a material handling system of smart electrical connectors workshop was discussed to verify the scheduling model and the speed control strategy combined with the MapReduce framework is feasible and effective to reduce the AGV path conflict probability. The material handling system could be applied in workshop to replace manual handling and to improve production efficiency.

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Coppini, Nivaldo Lemos, Aparecida de Fátima Castello Rosa, Alexandre Augusto Martins Carvalho, and Edson Melo de Souza. "Simulated Annealing Applied to Optimize the Efficiency of Flexible Manufacturing Cells." Applied Mechanics and Materials 778 (July 2015): 245–58. http://dx.doi.org/10.4028/www.scientific.net/amm.778.245.

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This work proposes a new methodology to optimize flexible manufacturing cells applying Simulated Annealing and Contribution Margin concepts. This methodology helps to determine the number of extra products that could be sold and manufactured while taking advantage of this idleness. The price formation to sell the extra products was based on contribution margin concepts. The main concept is to use cell idleness to increase profits while the costs are already paid. Equipment and workers have their fixed costs paid regardless of whether they are active or not. When they are not active, all of their costs are considered to be losses. What motivated the present work was the fact that, in general, the idleness detected in manufacturing processes does not receive adequate attention in the sense of taking advantage of it. To achieve this purpose, a program was developed to implement the methodology. This program generates user interfaces that allow the prediction of daily scheduling parts production. The first interface identifies only bottlenecks and idleness. The second interface, based on the Simulated Annealing (SA) metaheuristic technique, was designed to perform the management of idleness. A database was organized to present current and future daily scheduling parts production. Based on the volume of sales and the lead time of sold products, sellers are always able to update this database. Thus, the program can provide through its user interface, at any time, all of the information about production data for a specific schedule day that comes from the database. The user mentioned here is expected to be an industry salesman. Thus, it will always be possible to have previous knowledge about the bottlenecks and idleness that exist for any scheduled day in the future. This knowledge allows for planning the process of selling extra products made from the existing idleness. Two aspects were considered with respect to selling extra products that are produced via taking advantage of the idleness: the delivery time and the contribution margin of each product. To validate the program, a simulation was performed to determine which products should be produced during a scheduled day to ensure the delivery times or to ensure the maximum contribution margin, while considering the delivery time that is available. As a final consideration, the software can be considered to be functional and responsive to the possibility of profit maximization from the use of cell idleness.

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Larshin, Vasily Petrovich, Natalia V. Lishchenko, Olha B. Babiychuk, and Jan Pitel. "VIRTUAL REALITY AND REAL MEASUREMENTS IN PHYSICAL TECHNOLOGY." Applied Aspects of Information Technology 4, no. 1 (April 10, 2021): 24–36. http://dx.doi.org/10.15276/aait.01.2021.2.

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Information is transmitted by signals that have a material-and-energy nature, but it is not matter and not energy. The in-formation ensures communication of interacting objects of alive and inanimate nature. Information and communications technology underlie the new production paradigm called the “Industry 4.0”. In accordance with this paradigm, increased attention is paid to the pre-production phase on which relevant comprehensive solutions for the automation of design and production are taken, ranging from receiving an order for the product and ending with its shipment to the consumer. At the same time, issues of production management and efficient control of technological processes are solved, including scheduling and material requirement planning. At the pre-production phase, a virtual product is created (the information model of the real product in the form of a “virtual reality”), and at the execution phase a real (physical) product appears, which has a use value (possession utility). The implementation phase begins only after systemic computer modeling, simulation, and optimization of the technological process and operations, that is, after assessing both the time and the cost of virtual technological processes. In this regard, this research discusses topical issues of interaction between virtual information at the pre-production (preparatory) phase and new information arising at the implementation phase of physical technology in terms of improving the efficiency of computer-integrated production. It is shown that the information is a basic category not only in information (virtual) technology for its transformation and transmission, but also in physical technology of material production at the stage of manufacturing the appropriate material product, on the one hand, and (by analogy) in the process of distance learning of specialists, on the other hand (although information is not knowledgeable yet). Particular attention is paid to measuring procedure and assessing its accuracy; this work is not formal and requires the use of an intellectual system to ensure the accuracy of the information received.

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Belkaid, Fayçal, Farouk Yalaoui, and Zaki Sari. "An Efficient Approach for the Reentrant Parallel Machines Scheduling Problem under Consumable Resources Constraints." International Journal of Information Systems and Supply Chain Management 9, no. 3 (July 2016): 1–25. http://dx.doi.org/10.4018/ijisscm.2016070101.

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In present manufacturing environment, the reentrant scheduling problem is one of the most important issues in the planning and operation of production systems. It has a large scope such as capacity distribution and inventory control. On the other hand, the markets are very competitive; it is a critical requirement of operational management to have effective management of resources (consumable and renewable) so as to achieve optimal production plan. This study considers a reentrant parallel machines scheduling problem with consumable resources. Each job consumes several components and must be processed more than once in a stage composed of identical parallel machines. The resources availability, jobs assignment and sequencing at each cycle and are considered and optimized simultaneously. On the basis of this representation, a MILP model is developed. Thus, that MILP model can be used for the problem in order to find the exact solution. Since, this problem is clearly NP-hard, and optimal solutions for large instances are highly intractable, a genetic algorithm is developed to obtain near-optimal solution. Then, an improvement phase based on different local search procedures are performed and examined to generate better solutions. The system performances are assessed in terms of measures such as the solution quality and the execution time. The effectiveness of the proposed metaheuristic is examined based on comparative study. The simulation results demonstrate that the presented algorithm is able to find an optimal solution for small-sized problems and can effectively find a near optimal solution for large-sized problems to minimize the makespan of the considered problem.

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Fattahi, Parviz, Naeeme Bagheri Rad, Fatemeh Daneshamooz, and Samad Ahmadi. "A new hybrid particle swarm optimization and parallel variable neighborhood search algorithm for flexible job shop scheduling with assembly process." Assembly Automation 40, no. 3 (January 20, 2020): 419–32. http://dx.doi.org/10.1108/aa-11-2018-0178.

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Purpose The purpose of this paper is to present a mathematical model and a new hybrid algorithm for flexible job shop scheduling problem with assembly operations. In this problem, each product is produced by assembling a set of several different parts. At first, the parts are processed in a flexible job shop system, and then at the second stage, the parts are assembled and products are produced. Design/methodology/approach As the problem is non-deterministic polynomial-time-hard, a new hybrid particle swarm optimization and parallel variable neighborhood search (HPSOPVNS) algorithm is proposed. In this hybrid algorithm, particle swarm optimization (PSO) algorithm is used for global exploration of search space and parallel variable neighborhood search (PVNS) algorithm for local search at vicinity of solutions obtained in each iteration. For parameter tuning of the metaheuristic algorithms, Taguchi approach is used. Also, a statistical test is proposed to compare the ability of metaheuristics at finding the best solution in the medium and large sizes. Findings Numerical experiments are used to evaluate and validate the performance and effectiveness of HPSOPVNS algorithm with hybrid particle swarm optimization with a variable neighborhood search (HPSOVNS) algorithm, PSO algorithm and hybrid genetic algorithm and Tabu search (HGATS). The computational results show that the HPSOPVNS algorithm achieves better performance than competing algorithms. Practical implications Scheduling of manufacturing parts and planning of assembly operations are two steps in production systems that have been studied independently. However, with regard to many manufacturing industries having assembly lines after manufacturing stage, it is necessary to deal with a combination of these problems that is considered in this paper. Originality/value This paper proposed a mathematical model and a new hybrid algorithm for flexible job shop scheduling problem with assembly operations.

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Maropoulos, P. G. "Cutting Tool Selection: An Intelligent Methodology and its Interfaces with Technical and Planning Functions." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 206, no. 1 (February 1992): 49–60. http://dx.doi.org/10.1243/pime_proc_1992_206_055_02.

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This paper presents a new cutting tool selection methodology, namely the intelligent tool selection (ITS), which covers the whole spectrum of tool specification and usage in machining environments. The selection process has five distinct levels and starts by deriving a local optimum solution at the process planning level, which is progressively optimized in the wider context of the shop-floor. Initially, multiple tools are selected for each machining operation and tool lists are formed by sorting selected tools in order of preference. The second selection level provides a tooling solution for a component by considering all the operations required as well as the characteristics of the machine tool. The selected tools are then rationalized by forming a set of tools for machining a variety of components on a given machine tool at level 3 and by increasing the use of common and standard tools within a group of machines at level 4. Finally, the fifth level aims at reducing tool inventory by classifying existing tools into categories according to their usage and is also used for introducing new tools into the manufacturing system. The selection method allows the implementation of the minimal storage tooling (MST) concept, by linking the ordering of new and replacement tools to production control. ITS also uses the concept of tool resources structure (TRS), which specifies all tooling resources required for producing a component. By using the framework provided by ITS, TRS and MST it can be shown that tooling technology interfaces with diverse company functions from design and process planning to material/tool scheduling and tool management. The selection methodology results in higher utilization of tools, improved efficiency of machining processes and reduced tool inventory.

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Sharma, Vikram, Amit Rai Dixit, and Mohammad Asim Qadri. "Empirical assessment of the causal relationships among lean criteria using DEMATEL method." Benchmarking: An International Journal 23, no. 7 (October 3, 2016): 1834–59. http://dx.doi.org/10.1108/bij-08-2014-0078.

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Purpose It is difficult for anyone to implement all the lean tools simultaneously. One of the core issues is identifying critical criteria for the successful implementation of lean manufacturing (LM) and evaluating them. The purpose of this paper is to analyze the causal relationships of LM criteria in a machine tool manufacturing firm located in national capital region of India using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. Design/methodology/approach The research paper presents a blend of theoretical framework and practical applications. Based on literature review, 17 LM criteria were extracted that were validated by experts. A questionnaire was developed that was answered by experts serving in the XYZ machine tool manufacturing firm. Then, the DEMATEL method was applied to analyze the importance of criteria and the casual relations among the criteria were developed. Findings Using DEMATEL, the lean criteria were divided into cause group and effect group. In this study, information technology, computer-integrated manufacturing, enterprise resource planning, training, fixed position layout, smart processes and automation and concurrent engineering were classified in the cause group. Just in time, value stream mapping, 5-S, single minute exchange of die, visual control, job scheduling, standardized work, cellular manufacturing, poka-yoke, and total quality management were categorized in the effect group. The DEMATEL framework indicates that “training” is the most influencing factor for the lean implementation process in machine tool sector. Originality/value To know the key lean criteria and relationship among them can help many organizations to develop lean competencies. If the authors want to obtain high performance in terms of the effect group factors, it would be necessary to control and pay a great deal of attention to the cause group factors beforehand. This study is perhaps among the first few with focus on segmenting the set of lean criteria into some meaningful portions in order to effectively facilitate its implementation. The paper provides useful insights to the lean production implementers, consultants, and researchers.

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Márkus, A., J. Váncza, T. Kis, and A. Kovács. "Project Scheduling Approach to Production Planning." CIRP Annals 52, no. 1 (2003): 359–62. http://dx.doi.org/10.1016/s0007-8506(07)60601-5.

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McDonald, Conor M., and Iftekhar A. Karimi. "Planning and Scheduling of Parallel Semicontinuous Processes. 1. Production Planning." Industrial & Engineering Chemistry Research 36, no. 7 (July 1997): 2691–700. http://dx.doi.org/10.1021/ie960901+.

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Ge, Congqin, and Zhihong Yuan. "Production scheduling for the reconfigurable modular pharmaceutical manufacturing processes." Computers & Chemical Engineering 151 (August 2021): 107346. http://dx.doi.org/10.1016/j.compchemeng.2021.107346.

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Numao, Masayuki. "An integrated scheduling/planning environment for petrochemical production processes." Expert Systems with Applications 8, no. 2 (April 1995): 263–73. http://dx.doi.org/10.1016/0957-4174(94)e0017-o.

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Burcher, Peter. "Master Production Scheduling and Capacity Planning: The Link?" Integrated Manufacturing Systems 3, no. 4 (April 1992): 16–22. http://dx.doi.org/10.1108/09576069210018925.

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BONNEY, M. C. "Production Planning and Scheduling—mathematical Programming Applications." International Journal of Production Research 23, no. 5 (September 1985): 1053. http://dx.doi.org/10.1080/00207548508928075.

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Perkins, James R. "Optimal flow control in manufacturing systems: production planning and scheduling." Automatica 37, no. 9 (September 2001): 1499–500. http://dx.doi.org/10.1016/s0005-1098(01)00107-8.

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Tabucanon, Mario T., and Surat Petchratanaporn. "Tyre Manufacturing: Simplifying a Complex Production Planning and Scheduling Problem." Logistics Information Management 4, no. 3 (March 1991): 10–14. http://dx.doi.org/10.1108/eum0000000002878.

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Buckley, J., A. Chan, U. Graefe, J. Neelamkavil, M. Serrer, and V. Thomson. "An integrated production planning and scheduling system for manufacturing plants." Robotics and Computer-Integrated Manufacturing 4, no. 3-4 (January 1988): 517–23. http://dx.doi.org/10.1016/0736-5845(88)90024-5.

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HIGGINS, PAUL, and JIM BROWNE. "Master production scheduling: a concurrent planning approach." Production Planning & Control 3, no. 1 (January 1992): 2–18. http://dx.doi.org/10.1080/09537289208919369.

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Dvorak, Filip, Maxwell Micali, and Mathias Mathieug. "Planning and Scheduling in Additive Manufacturing." Inteligencia Artificial 21, no. 62 (September 7, 2018): 40. http://dx.doi.org/10.4114/intartif.vol21iss62pp40-52.

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Recent advances in additive manufacturing (AM) and 3D printing technologies have led to significant growth in the use of additive manufacturing in industry, which allows for the physical realization of previously difficult to manufacture designs. However, in certain cases AM can also involve higher production costs and unique in-process physical complications, motivating the need to solve new optimization challenges. Optimization for additive manufacturing is relevant for and involves multiple fields including mechanical engineering, materials science, operations research, and production engineering, and interdisciplinary interactions must be accounted for in the optimization framework. In this paper we investigate a problem in which a set of parts with unique configurations and deadlines must be printed by a set of machines while minimizing time and satisfying deadlines, bringing together bin packing, nesting (two-dimensional bin packing), job shop scheduling, and constraints satisfaction. We first describe the real-world industrial motivation for solving the problem. Subsequently, we encapsulate the problem within constraints and graph theory, create a formal model of the problem, discuss nesting as a subproblem, and describe the search algorithm. Finally, we present the datasets, the experimental approach, and the preliminary results.

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Yan, Hong-Sen, Qi-Feng Xia, Min-Ru Zhu, Xia-Ling Liu, and Zhi-Min Guo. "Integrated Production Planning and Scheduling on Automobile Assembly Lines." IIE Transactions 35, no. 8 (August 2003): 711–25. http://dx.doi.org/10.1080/07408170304348.

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Hill, John, Ricardo Costa, and Eduardo Jardim. "Strategic Capacity Planning and Production Scheduling in Jobbing Systems." Integrated Manufacturing Systems 3, no. 3 (March 1992): 22–26. http://dx.doi.org/10.1108/09576069210015874.

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Kopanos, Georgios M., Luis Puigjaner, and Christos T. Maravelias. "Production Planning and Scheduling of Parallel Continuous Processes with Product Families." Industrial & Engineering Chemistry Research 50, no. 3 (February 2, 2011): 1369–78. http://dx.doi.org/10.1021/ie100790t.

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Toivonen, V., K. Ikkala, E. Niemi, and A. Korhonen. "Planning and Scheduling System for Make-To-Order Production." CIRP Annals 55, no. 1 (2006): 493–96. http://dx.doi.org/10.1016/s0007-8506(07)60466-1.

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Váncza, J., T. Kis, and A. Kovács. "Aggregation - the key to integrating production planning and scheduling." CIRP Annals 53, no. 1 (2004): 377–80. http://dx.doi.org/10.1016/s0007-8506(07)60720-3.

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Journal articles on the topic 'Manufacturing processes. Production planning. Production scheduling'

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