Dissertations / Theses on the topic 'Process Optimization'

The theoretical part will be focused on presenting information within the process management. Some of the pieces of this theoretical information will be were slightly modified by internal Continental procedures and applied in the practical part of the thesis in order to redesign current purchasing process of non production material. The contents of the practical part of this thesis are the analysis of the current purchasing process of non-production material in the plant of Continental. The intention is to identify the waste and obstacles in the process. The main target is to improve the process in consideration of efficiency, lead time reduction and, if applicable, cost savings. Once the waste in the process is identified, the 100% value added ideal state is going to be developed, under consideration of implementing the improvements, which have been identified in the current state. Based on the differences between the current state and the ideal state of the process, the future state is going to be mapped.

Increasing interest to optimization of goods incoming process has paralleled the rise of product diversity and advanced warehouse management based on logistics support systems. Nowadays, companies are universally faced with the requirements to reengineer their business processes starting with goods incoming operation, aiming to significantly reduce total operating costs and quickly respond to ultimate consumer. Previous academic research has provided many alternatives to attain the expected results. Nevertheless, an enormous gap still exists between theoretical research and practical operations. The purpose of this paper is to bridge this gap from operation level.We introduced a theoretical framework which was organized around earlier studies, latest findings and established literatures associated with overview of goods incoming process, flows management, seven wastes, logistics support systems etc. Meanwhile, an online fashion retailer, Nelly.com goods incoming process has been mapped from goods receiving, packing and sorting, warehousing to data input. As a result, intermittent material flows and information flows has been realized. Later on, a sensitivity analysis was performed to observe all wastes in the process through precise timing of each detailed activity. As the weaknesses and opportunities have been identified within Nelly’s goods incoming process, some heuristic solutions were proposed in the paper.Generally, flows should be smoothed and accelerated, particularly material flows and information flows related with goods incoming process. The interruption and miscommunication should be avoided to streamline the whole operation. Whilst, we inferred that all wastes within every sub-process have to be aware of. Consequently, some techniques such as scheduled delivery, cross-docking, goods classification, improved logistics support systems were proposed to eliminate wastes. Further on, the prevailed business process reengineering should be conducted as the next step to reallocate some resources or operations.Lastly, we simulated an expected goods incoming process based on Nelly’s status quo and heuristic suggestions. And some future research issues have been presented at the end to extend the vision to relevant domains.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2007.<br>Includes bibliographical references (p. 69-70).<br>Novartis is one of the largest pharmaceutical companies in the world, with their research headquarters (Novartis Institutes for BioMedical Research) located in Cambridge MA. In this thesis, I explore Novartis's process for developing drugs, specifically the earlier stages of research leading to high throughput screening. During the course of a 6.5 month, on-site project, Novartis's processes were identified, data were collected and relevant literature in product development and organizational structure were surveyed. Based on the accumulation of this information, several opportunities for improvement were identified and from these, recommendations were developed and implemented. This thesis considers the improvements Novartis could see in their drug discovery process by improving communication between organizations. In particular, I suggest that the company could benefit in cycle time and quality by designing and following more robust lateral processes and by moving their communication mode closer to integrative problem solving.<br>(cont.) Following these recommendations, I investigated why Novartis did not already have these processes in place. I hypothesize that the main reason for this is because the research organization at Novartis is focused primarily on exploration, therefore their ability and need to coordinate has not been an area of focus. Novartis has made a very deliberate effort to design an organization that promotes novel drug discovery; perhaps sacrificing cycle time and process efficiency. Because of this strong focus on drug discovery, Novartis has not had opportunity to design and implement efficient processes. By bring in interns from MIT's Leaders for Manufacturing Program, the company is beginning to explore ways to improve their processes without sacrificing their ability to develop novel drugs.<br>by Rebecca Anne Roberts.<br>S.M.<br>M.B.A.

Les procédés de séparation membranaire sont une technologie bien connue et déjà largement utilisée dans le domaine de la purification des gaz. Ces procédés sont applicables à de nombreux secteurs d’activités industriels. Selon les performances de séparation recherchées, elles peuvent constituer une alternative intéressante aux technologies existantes de traitement des gaz (adsorption, cryogénie, contacteurs gaz/liquide). Pour exploiter au mieux cette technologie, le développement d'outils d’aide à la décision permettant d’identifier les procédés et les conditions opératoires économiquement avantageux est absolument nécessaire. Bien que les approches expérimentales d'optimisation appliquées à différentes études de cas conservent un intérêt certain, une approche générale et sa validation dans le cadre de différentes études de cas font toujours défaut. L’objectif principal de cette thèse est de développer un outil numérique le plus générique possible d’optimisation de procédés de séparation membranaire. Dans ce travail, la synthèse du procédé membranaire est traitée et modélisée comme un problème d'optimisation mathématique non linéaire et non convexe basé sur un paradigme de superstructure couvrant une combinatoire d'unités (modules membranaires, compresseurs, pompes à vide) et de connexions la plus exhaustive possible. Des fonctions de coûts réalistes et détaillées sont utilisées comme fonction objectif dans l'optimisation. Une stratégie d'optimisation globale continue, qui peut se considérer comme la composition de deux algorithmes : Multistart et Monotonic Basin Hopping (MBH) ; est présentée pour résoudre le problème d'optimisation susmentionné. L'efficacité de cette démarche d'optimisation est dans un premier temps validée en comparant sa solution à celles présentées dans la littérature. La méthode proposée est ensuite appliquée à l'optimisation de plusieurs cas emblématiques de la séparation de gaz (CO2 de gaz de haut fourneaux, séparation O2/N2 de l’air, traitement du biogaz et du gaz naturel). Différents degrés de liberté du système sont permis et analysés selon les cas (pressions variables, type de membrane variable). L'analyse détaillée des résultats est discutée en termes d’architecture de procédés et de distribution des coûts (CAPEX, OPEX)<br>Membrane separation is a well-known technology in gas purification, which is applicable in different aspects of the industry. Over the last decades, depending on the required separation performances, it became a viable alternative to several gas separation technologies (adsorption, cryogenics, gas /liquid contactors). To exploit at best this technology, nevertheless, tools to find cost-effective designs and operating conditions are necessary. While experimental optimization approaches applied to different case studies have been investigated extensively, a more generic optimization approach and its validation along different case studies are still missing. The work of this thesis starts with this key observation and tries to fill this gap. The membrane process synthesis is modelled as a nonlinear and non-convex mathematical optimization problem based on a superstructure paradigm covering a wide range of possible units (membrane modules, compressors, and vacuum pumps) and connections as exhaustive as possible. Realistic and detailed cost functions are used as the objective in the optimization. A continues global optimization strategy, that can be considered as the composition of two algorithms: Multistart and Monotonic Basin Hopping (MBH); is presented to solve the aforementioned optimization problem. The efficiency of this overall optimization approach is, first, validated by comparing its solution with the ones presented in the literature. Then, the proposed method is applied to the optimization of several important gas separation cases (CO2 recovery from blast furnace gas, O2/N2 air separation, and biogas and natural gas purification) by increasing the membrane system degree of freedom step by step. Detailed analysis of the results is discussed in terms of process architecture and cost distribution (CAPEX, OPEX)

Blast furnace is the heart of every steel plant. Steel production is based on the blast furnace process, as it is where the iron is extracted from the iron ore and turned into liquid iron, which will subsequently be used to make liquid steel. Therefore, without hot iron, steel can not be produced. Blast furnaces in this process are supplied among others with pulverized coal. Raw coal should be prepared for the blast furnaces in the form of fine coal powder. This fine coal powder should then be injected into the blast furnaces in order to continue the production. This process is carried out by the Pulverized Coal Injection System, which changes raw coal into dry fine coal powder. The system consists of a hot gas generator, a coal mill, a bagfilter as well as various valves, fans and piping. The general idea is to burn specific gases with the help of equipments and to use them to dry the coal in the cycle. When the amount of the gases inserted into the system is changed, the dried coal amount is directly affected. Based on this background the following project is carried out, which aims at the investigation of bottlenecks and critical points in the process. The most important bottleneck is the limited possibility of fresh air usage, as the oxygen in fresh air can cause explosions if existent in exceeding amounts in the system and thus, is dangerous. In order to prevent this explosive condition in the system, additional gases need to be added to the system. The aim of this project is to introduce additional gases to the system in order to increase the upper limit of the fresh air amount. Increasing the amount of fresh air in the recirculation gas should provide more amount of dried coal,hence increasing the drying capacity of the coal grinding plant. To understand the situation better, tests about gas injection are carried out in the system. The results of the tests are analyzed and the performance changes in the system are calculated. For this, programs in Excel and also inLabVIEW are created to interpret the situations easily. As it is understood from the results of the tests, when the amount of the additional gases isincreased, approximately 10% increase in the amount of dried coal is observed. Subsequently, Pulverized Coal Injection mill productivity isincreased. Additionally, oxygen percentage in the mill circuit will decrease and this is important for the safety conditions. To conclude, this project aims to show the usage and recycling of additional gases in “PulverizedCoal Injection” process by implying various programs and interpretations.

Gas nitriding is an important thermochemical surface treatment that is used to improve the wear and corrosion resistance as well as the fatigue endurance of steel parts. Accurate process control is the effective way to ensure the properties reliability of nitriding process. To realize the accurate process control, the nitriding process parameters need to be modeled and controlled to meet the specifications. There has been ongoing effort on the simulation of the gas nitriding process since 1990s. However, most of the work has been done to simulate the gas nitriding process of pure iron due to the limited thermodynamics and kinetics information available on the gas nitriding process of steels. The objective of this project is to develop an accurate and user friendly software model to simulate the gas nitriding process of steels based on the fundamental understanding of thermodynamics and kinetics. In this work, the customized Lehrer diagram which describes the phase stabilities in specified steel as a function of nitriding potential and temperature has been successfully constructed by computational thermodynamics for the first time. Based on the Lehrer diagrams for steels, the compound layer growth model is proposed to simulate the gas nitriding process of steels. By using this model, the properties of the nitrided steels based on the phase constitution, surface nitrogen concentration, nitrogen concentration profile, case depth, as well as growth kinetics can be simulated as a function of the process parameters (temperature, time, and the nitriding atmosphere). The results of the model are in excellent agreement with experimental results.

An experimental study was carried out concerning the optimization of catalyst type, operating conditions, addition of water and hydrogen for use in the THAI-CAPRI process and is reported. Three feeds namely, THAI field oil, Combustion Cell Oil (CCO) and n-decane were used in the presence of catalyst or an inert medium for comparison. Experiments were carried out using micro-reactors containing 5 g catalyst under different temperatures, pressures and gas environments. It was found that there was a trade-off in operation temperature between upgrading performance and catalyst lifetime. At higher temperatures of 500 °C led to an average of 6.1 °API upgrading , however, the catalyst lifetime was limited to 1.5 hours. Operation at 420 °C was found to be a suitable compromise, with upgrading limited up to 3 °API, with catalyst lifetime extended to 77.5 hours. From the results of the current study it can be said that by careful control of the temperature and oil flow rate in the in-situ CAPRI process, additional upgrading compared with the THAI process alone may be effected, resulting in a more valuable produced oil, which is easier to transport and could be further processed into distillates.

The work of the Thesis has been pursued in collaboration with an important company operating in the tourist sector. The followed projects in the work can be seen as belonging to the Destination Management branch, that is the study and the implementation of actions aimed at better managing the company offer related to touristic experiences broadly. In particular, the first project has been related to Revenue Forecasting and has dealt with the definition of a methodology, based on mathematical and statistical techniques, aimed at forecasting the revenue streams linked to specific items of a company; the second project, Destination Discovery, instead aimed at the high-level analysis of tourism opportunities in different geographical areas, researching and evaluating new possibilities for the company related to tourist interest. In the work, some preliminaries about what a forecast is will be provided and the many techniques aimed at accomplishing the task, giving a general theoretical framework for the topic will be discussed. Then some details about data and the set of more practical operations needed in order to extract information from them in a numerical manner, eventually building a forecasting model on it will be discussed. Later the application of the techniques previously introduced to the different projects will be discussed; for each one of them, the methodologies followed and the analyzes carried out will be provided, as well as the obtained results. Finally an analysis of what has globally been done in the work along with different comments, the obtained results and some possible future work and improvements will conclude the work.

High quality scrap is the dream of all the smelters but it is expensive. Therefore low quality scrap has also to be re-melted. Here two strategies have to be taken into account: increasing the scrap quality inside the refinery and removing the non-metal content during the re-melting of the scrap The aim of this doctoral thesis is to support the aluminium recycling industry in both these aspects highlighting the influence of the pre-melting scrap treatments and the melting practices on the effectiveness of the recycling process in terms of metal recovery.<br>I rottami di alta qualità sono i più facile da riciclare, ma anche i più costosi. Due vie sono percorribili per rendere possibile il riciclo di rottami con un alto livello di elementi non desiderati: aumentarne la qualità attraverso appositi trattamenti pre-fusione e rimuovere il contenuto non metallico durante la rifusione Scopo di questa tesi di dottorato è quello di sostenere l'industria del riciclaggio dell'alluminio in entrambi questi aspetti, evidenziando l'influenza dei trattamenti pre-fusione del rottame e delle pratiche di fusione sull'efficacia del processo di riciclaggio in termini di resa metallica del processo stesso.

Master thesis focuses on payment process automatization of selected company XY, which will eliminate repetitive manual work and routine and will lead to shortening of the whole process. To reach this solution RPA – Robotic Process Automation was used. RPA was designed based on data analysis, which showed areas of process best suited for automatization. Part of the thesis is also evaluation of impacts of implemented RPA solution.

The thesis is focused on the identification of service and administrative processes and sub processes inside the chosen company and proposal of their possible separation and outsourcing using the Business Process Management methods. Potential changes should be aimed to release capacity of the monitored team of the company and optimize their processes and related capacity during busy season and also from the long term perspective. The company set the conditions for potential changes by keeping current standards about quality of products and services and keeping current rules for client communication. Additionally company expects decreasing of personal costs related to inquired services.

Thesis deals with application of process management in a selected company. The first chapters outline the situation in the area of process management. Dealing with the history of process management, then describe the general processes that take place in companies, and a procedure in which the company usually introduces process management. The second part attends to application of process management in to company AVEX. First there is the company description, the SWOT analysis, from which come business objectives. The last part deals with the practical application of process management.

Thesis deals with design process optimization at Chute Corporation -- american startup that provides SaaS solutions for discovery, gathering, managing, publishing and analysis of multimedial user-generated content from social networks. The goal is to identify and analyze the processes, roles and tools of product design and propose an optimization. Thesis has two parts. First part describes the theoretical background for later application. Mainly a brief history of IT product design, design taxonomy and design workflow best practices are described. The other part provides a brief description of the company, especially its position on the market, business model, organizational structure, product portfolio, position of product team and also identifies the main processes, roles and tools that surround product design. The final part describes all optimized processes, roles and tools and summarizes all the facts as a set of recommendations. Thesis provides an overview of product design in the dynamic and complex world of startups. The specific recommendations and templates of optimized processes and tools enable immediate implementation into a company of a similar nature.

Finish machining of hardened steel is receiving increasing attention as an alternative to the grinding process, because it offers comparable part finish, lower production cost, shorter cycle time, fewer process steps, higher flexibility and the elimination of environmentally hazardous cutting fluids. In order to demonstrate its economic viability, it is of particular importance to enable critical hard turning processes to run in optimal conditions based on specified objectives and practical constraints. In this dissertation, a scientific and systematic methodology to design the optimal tool geometry and cutting conditions is developed. First, a systematic evolutionary algorithm is elaborated as its optimization block in the areas of: problem representation; selection scheme; genetic operators for integer, discrete and continuous design variables; constraint handling and population initialization. Secondly, models to predict process thermal, forces/stresses, tool wear and surface integrity are addressed. And then hard turning process planning and optimization are implemented and experimentally validated. Finally, an intelligent advisory system for hard turning technology by integrating experimental, numerical and analytical knowledge into one system with user friendly interface is presented. The work of this dissertation improves the state of the art in making tooling solution and process planning decisions for hard turning processes.

The process industries are characterized by the enormous use of natural resources such as raw materials, solvents, water, and utilities. Additionally, significant amounts of wastes are discharged from industrial facilities. As the world moves toward sustainable progress, that is, meeting the demand of the current generation without affecting or compromising the new generation, future process facilities must focus on resource conservation and pollution prevention. The purpose of this work is to introduce a new process integration methodology for the conservation and optimization of resources in the process industries. The work is also geared towards reducing waste discharge from the processing facilities. The optimal management of fresh resources and waste disposal requires the appropriate allocation, generation, and separation of streams and species. Material recycle/reuse/substitution, reaction alteration, and process modification are some of the main strategies employed to conserve resources in the process industries. The overall problem addressed in this dissertation can be stated as follows: Given is a process with a number of streams (sources) that are characterized by certain criteria (e.g., compositions of certain compounds, targeted properties) where these streams can be utilized in a number of process units (sinks) if they satisfy given constraints on flow rate, compositions, and/or properties. Additionally, interception devices may be used to adjust stream criteria. The objective is to develop targeting procedures and synthesis tools for the identification of minimum usage of fresh resources, minimum discharge of waste, and maximum integration of process resources. The devised methodology addresses four classes of problems: • Targeting techniques using direct recycle strategies • Recycle and interception procedures for single-component systems • Recycle and interception procedures for multi-component systems • Property integration for direct recycle strategies The framework provided by this dissertation couples traditional mass integration with groundbreaking property integration techniques to target, synthesize and optimize a plant for maximal conservation of resources. In particular, this work introduces new techniques such as material recycle pinch analysis, simultaneous recycle and interception networks, and property-based allocation. Additionally, graphical, algebraic, and optimization approaches are developed and validated with case studies in order to illustrate the applicability of the devised procedures.

In this work, a method is presented for estimating the likely economic benefit from installing a steady state on-line optimizer on a plant. The objective of an online optimization scheme is to track the real process optimum as it changes with time. This must be achieved while allowing for disturbances to the process, ensuring process constraints are not violated. The benefit gained depends on the structure of the on-line optimizer. This structure includes the measurements used for the estimation of model parameters, parameters estimated in the model and the variables which are used as set points for passing the optimization results to the regulatory control level of the process. Using the estimate of the economic benefit, the "best" structure of the optimizer can be determined. The disturbances to the process have be described by both statistical and deterministic means. With a given disturbance description and set of structural decisions, an average economic return for the process with on-line optimization can be estimated. This average is found using a second order Taylor series expansion of the non-linear process model at a nominal operating condition. The average economic return of the process can be directly traded off against the cost of the necessary equipment for installing a particular on-line optimizer (i.e. instrument costs). Two sets of examples are presented. In the first set of examples all of the process model structures can be captured using the second order Taylor series expansion. These examples are used to demonstrate the different features of the analysis of an on-line optimization structure. The second set of examples demonstrates the analysis on a model of the Williams-Otto plant. This case study is used to test the procedure on a non-linear case study. The results generated are compared against Monte Carlo simulations of the non-linear process. Finally there is a discussion and summary of the conclusions from examples and suggestions for potential areas for further research.

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2012.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 58).<br>The primary goal of this project is to evaluate Amazon's inbound supply chain processes and identify improvement opportunities in transportation cost and lead time. Analysis will be focused on defining the current state and evaluating the strengths and weaknesses of the inbound processes. This paper will also include a literature review of the various freight consolidation and vendor coordination strategies in the industry and their impact on cost and lead time. Specific case studies based on actual cost savings programs will be discussed.<br>by Chong Keat Ng.<br>M.B.A.<br>S.M.

The purpose with this thesis is to reduce downtime of machines androbots in a serial production line by improving communication betweenoperators and machines. Modeling a serial production line asa queuing system makes Markov chain optimization methods possible.The concept is to make machines and robots adapt its service ratesbased on status of its surrounding machines and the position of operators.In a pharmaceutical industry, a production rate of 50-60% of itsmaximum capacity is considered as normal. Unnecessary downtimecaused by machine breakdowns is one factor which reduces the productionrate. Two optimization methods were investigated, the workallocation problem and the targeting problem. It was found that thework allocation problem does not provide an optimal solution whenmodeling with a saturated model. The targeting problem provides anoptimal solution, which is a trade-off between the average amount ofproducts in a system and the cost for keeping this level.<br>Målet med detta examensarbete är att minimera driftstopp i en seriellproduktionlina genom att förbättra kommunikationen mellan operatöreroch maskiner. Genom att modellera en produktionslina somett kösystem möjligör användandet av optimeringsmetod för markovkedjor.Konceptet är att låta maskiner och robotar anpassa sin produktionshastighetbaserat på positionen av operatörer. Inom läkemedelsindustrinär en produktionshastighet om 50-60% av den maximala kapacitetenansedd som normalt. Onödigt långa driftstopp i sambandmed maskinfel är en faktor som påverkar produktionshastigheten. Tvåoptimeringsmetoder studerades, Åork Allocation Problemöch TargetingProblem". Det visades att det inte var möjligt att hitta en optimallösning med hjälp av Åork Allocation Problem". Targeting Problemggeren optimal lösning som är en avvägning mellan det genomsnittligaantalet produktion i ett system och kostnaden för att hålla den nivån.

Embedded systems which are targeted towards portable applications are required to have low power consumption because such portable devices are typically powered by batteries. During the memory accesses of such battery operated portable systems, including laptops, cell phones and other devices, a significant amount of power or energy is consumed which significantly affects the battery life. Therefore, efficient and leakage power saving cache designs are needed for longer operation of battery powered applications. Design engineers have limited control over many design parameters of the circuit and hence face many chal-lenges due to inherent process technology variations, particularly on static random access memory (SRAM) circuit design. As CMOS process technologies scale down deeper into the nanometer regime, the push for high performance and reliable systems becomes even more challenging. As a result, developing low-power designs while maintaining better performance of the circuit becomes a very difficult task. Furthermore, a major need for accurate analysis and optimization of various forms of total power dissipation and performance in nanoscale CMOS technologies, particularly in SRAMs, is another critical issue to be considered. This dissertation proposes power-leakage and static noise margin (SNM) analysis and methodologies to achieve optimized static random access memories (SRAMs). Alternate topologies of SRAMs, mainly a 7-transistor SRAM, are taken as a case study throughout this dissertation. The optimized cache designs are process-voltage-temperature (PVT) tolerant and consider individual cells as well as memory arrays.

Wheat milling is a complex process, in terms of plant layout, interactions between processing units and high variability of feed materials. Despite the rapidly increasing diffusion of analytical instruments to characterize important wheat and flour properties (e.g., near-infrared spectrometers and image analysis sensors), current wheat milling processes are still poorly instrumented. Therefore, process operation is mostly based on the operators’ experience, and in most cases even the design of the process is based on experience only. On the other hand, severe quality requirements are usually set on the final product. The development of science-driven (as opposed to experience-driven) tools to support process understanding, design and operation can be very beneficial for those industries that require wheat milling as a part of their manufacturing process. Intelligent manufacturing through digitalization is a trend in current manufacturing systems. This Dissertation moves along this trend by proposing an integrated, model-based approach to the optimization of wheat milling processes. In particular, two complementary approaches are investigated: development of data-driven models for single processing units, and simulation of entire milling processes. The models of single units are used to tackle different issues that arise in the wheat milling operation: i) wheat classification, ii) process understanding, iii) prediction of product quality and iv) process design and scale-up. Regarding wheat classification, a methodology based on the analysis of near-infrared (NIR) spectra in combination with latent variable modeling is developed. The objective is checking the ability of NIR spectra to discriminate different wheat varieties, an important aspect of the wheat milling operation, given the high intrinsic variability showed by natural products as wheat. Wheat milling is a complex process which needs profound understanding to be operated in a satisfactory way. The analysis of the model parameters allows for a better comprehension of the breakage mechanism occurring in wheat milling, thus improving process understanding. The effect of the most influential process parameters and of the wheat properties onto the milled product characteristics is studied for different “passages” (i.e., combinations of processing units) of the process. Expensive and time-consuming experiments can be partly avoided exploiting the predictive ability of data-driven models, which can be used to predict the product quality (i.e., the particle size distribution or the mass fraction of the milled or sieved material), thus supporting the operators in process operation. In this Dissertation, data-driven models are used to predict the product quality both for roller mills and for plansifters. The problem of process design is related to the estimation of the process parameters to be used to obtain a product with a desired characteristic. Data-driven models provide a useful tool to this purpose, through the implementation of appropriate model inversion techniques. In this Dissertation, a latent variable model inversion methodology, that relies on an optimization framework and on data coming from different plant scales, is developed. The framework aims at suggesting the optimal process parameters to be used to obtain a product with desired properties, with the ultimate scope of accelerating the scale-up from the laboratory to the commercial plant. The development of a platform for the simulation of the whole milling process is started in this Dissertation. Due to the complexity of the wheat milling operation, the process is still open to optimization, in terms of both layout and power consumption. The objective is developing a simulator of the whole milling process, that aims at modeling the pneumatic transport, pressure drops and power consumption. This tool can be used to get a better comprehension of the energy consumed throughout the mill and to optimize the process layout, minimizing the overall power consumption.<br>La macinazione del grano è un’operazione complessa, sia a causa delle complicate interazioni tra le unità, che risultano in una complessa struttura del processo stesso, che a causa dell’alta variabilità intrinseca di un prodotto naturale come il grano. Per queste ragioni, la macinazione è un processo difficile da esercire. Nonostante la grande diffusione di strumenti analitici per caratterizzare importanti qualità del grano e della farina (come ad esempio spettrometri al vicino infrarosso o analizzatori di immagini), l’attuale processo di macinazione di grano è tutt’ora poco equipaggiato con tali strumenti. Perciò il controllo di processo è principalmente basato sull’esperienza degli operatori e nella maggior parte dei casi persino la progettazione del processo è empirica. Tuttavia, al prodotto finale è richiesto un alto livello di qualità. Le industrie che coinvolgono il processo di macinazione di grano possono beneficiare enormemente dello sviluppo di strumenti scientifici e sistematici (opposti a quelli empirici basati sull’esperienza) per assistere la comprensione, progettazione e l’operazione del processo. La produzione intelligente attraverso la digitalizzazione è la tendenza seguita dai moderni processi manifatturieri. Questa Tesi, assecondando la direzione indicata da questa tendenza, propone un approccio basato su modelli per ottimizzare il processo di macinazione di grano. A tal proposito, vengono esposti diversi approcci basati sulla modellazione matematica per assistere la macinazione di grano. In particolare, vengono considerati due approcci: modelli basati su dati delle singole unità di processo e simulazione dell’intero processo. I modelli delle singole unità di processo sono stati utilizzati per risolvere diversi problemi che caratterizzano l’operazione di macinazione: i) classificazione delle diverse varietà di grano, ii) comprensione del processo, iii) predizione della qualità di prodotto e iv) progettazione di processo e scale-up. La classificazione delle diverse varietà di grano è un aspetto cruciale del processo di macinazione di grano. A tal proposito è stata sviluppata una metodologia basata sull’analisi di spettri al vicino infrarosso combinata a modelli a variabili latenti, con l’obiettivo di testare le capacità discriminanti degli spettri. L’effettivo meccanismo di rottura del grano è ancora relativamente poco conosciuto, soprattutto a causa della complessità del processo stesso: acquisire una migliore comprensione del processo può essere di grande aiuto nell’esercire l’operazione di macinazione. L’analisi dei parametri del modello permette da un lato di acquisire una migliore comprensione del meccanismo di rottura del grano e dall’altro di studiare e quantificare l’effetto dei parametri di processo più influenti e delle proprietà del grano sulle caratteristiche del materiale macinato, per diversi passaggi del processo. Le capacità predittive dei modelli basati su dati possono essere sfruttate per predire la qualità del prodotto (ad esempio, la granulometria o la frazione massiva del prodotto setacciato), in modo da evitare costosi, sia in termini di risorse che di tempo, esperimenti. In questa Tesi, modelli basati su dati sono utilizzati per predire la qualità di prodotto sia per mulini a rulli che per i setacci piani. La progettazione di processo è la relativa al problema di stimare la migliore combinazione di parametri di processo che devono essere usati per ottenere un prodotto con la qualità desiderata. Una soluzione a questo problema è offerta dai modelli basati su dati, nel caso in cui vengano utilizzate appropriate tecniche di inversione di modello. In questa Tesi, è stata sviluppata una metodologia di inversione di modelli a variabili latenti che si basa su un problema di ottimizzazione che include dati provenienti da differenti scale del processo. L’obiettivo ultimo è suggerire i parametri di processo ottimali per ottenere un prodotto con una caratteristica desiderata, in modo da accelerare lo scale-up dalla scala di laboratorio a quella industriale. In questa Tesi, si è cominciato a sviluppare una simulazione dell’intero processo. A causa della sua complessità, l’attuale processo di macinazione di grano è ancora aperto ad interventi di modernizzazione e ottimizzazione, sia riguardo la struttura del processo che i consumi di energia. L’obiettivo è sviluppare un simulatore dell’intero processo di macinazione, con lo scopo di modellare il trasporto pneumatico, le perdite di carico e i consumi di energia del processo. Questo strumento può essere utilizzato per comprendere meglio le fonti principali di consumo di energia nel mulino e per ottimizzare la struttura del processo minimizzando, ad esempio, il consumo di energia.

Work theoretically and practically deals with process management - the process analysis and optimization of business processes in the company. The theoretical part describes the process control and its features and benefits, describes the term of process and the types of processes. The theoretical part also describes the theoretical basis of process analysis. At the end of the theoretical part is the explanation of the concept of business process optimization. In the practical part at first author presents company, which then performs a SWOT analysis of the company. Furthermore, in the practical part is a process analysis of selected business processes in EPC notation. After the analysis, followed by optimization - improve the business processes. The last point of this work is the evaluation of work and conclusion.

This thesis is focused on optimizing business processes in an environment of LIMAL (CZ). The aim of my work is to analyze and present the company processes and design new processes, which will be used to make the necessary adjustments in the information system and in the working practices of individual employees. The work is divided into two parts, theoretical and practical. The theoretical part describes the issue of business processes and their classification. Furthermore, usual methods which can be used to optimize business processes. The practical part is focused on optimizing the most important processes in LIMAL (CZ) s.r.o. First part clarify the company's activities and its specifics. To better understand the environment in which business operates, I present an Porter's analysis of competitive environment. The following part is an overview of each company's internal processes, and description of their current status and deficiencies, and proposed a new procedure, including the benefits that the deployment will bring. The work will serve as a reference for implementation of necessary changes in the information system and working practices of employees.

The thesis focuses on optimization of logistics processes in the company Vanad 2000 a.s. This company employs about fifty employees. Company is included among small companies from this reason. The logistics was chosen mainly because logistics has important role nowadays. Logistics is the main point to be different from the other companies and to gain a competitive advantage. Selected processes are described in this thesis. At these processes is designed optimization. We can find selected processes which are determined for optimization in this thesis. These processes are graphically displayed using BPMN diagram in the next part. The aim of dissertation is properly analyze selected processes and suggest a real solution of their optimization

Il documento presentato punta alla descrizione del lavoro svolto dal DEI in collaborazione con l'azienda Marini-Fayat la quale ha sviluppato un prototipo innovativo per l'essiccazione di asfalti. L'obiettivo di tale collaborazione ha riguardato principalmente attività di studio della letteratura circa il processo di essiccazione degli asfalti, la sua modellazione e il controllo dell'intero impianto rispettandone i vincoli imposti. Il lavoro si svolto nel seguente modo, dopo lo studio della letteratura sull'argomento, due tipologie di modello sono state sviluppate: un "Evaluation model" che divideva l'impianto in sezioni concatenate di lunghezza fissata e voleva descrivere in maniera fine i comportamenti fisici del sistema, a questo si è aggiunto lo sviluppo di un "control model" con l'obiettivo di riportare solo i fenomeni principali di questo processo di essiccazione, portando così a una maggiore leggerezza computazionale. Al fine di testare le azioni di controllo si sono pensati degli esperimento per la stima dei parametri di sistema. Una volta noti tali parametri è stato possibile convalidare l'effettiva funzionalità dei controllori sviluppati sul più leggero e performante "control model" con ottimi risultati.

Production systems typically involve significant uncertainty in their operation due to either external or internal sources. The existence of uncertainty transforms conventional deterministic process models to stochastic/parametric problems, the solution of which requires the application of specialized optimization techniques. The main objective of this thesis is to develop suitable algorithms and numerical techniques for the efficient solution of process engineering problems involving uncertain parameters. Based on modelling issues regarding uncertainty classification (deterministic and stochastic uncertain parameters) and design objectives with respect to uncertainty (fixed degree of flexibility and optimal degree of flexibility), a unified multiperiod/stochastic two-stage optimization formulation is proposed and a decomposition based algorithmic procedure is developed for its efficient solution. The proposed algorithm forms the basis for addressing process design problems, planning and scheduling problems and problems related to behavioural analysis under uncertainty. For batch plant design problems involving uncertainty in the description of process parameters such as transfer coefficients, kinetic constants, etc., as well as variability of external parameters such as product demand, economic cost data etc., the exploitation of the special structure coupled with the relaxation of feasibility requirement regarding product demands enables the transformation of the stochastic two-stage programming problems to a single optimization model where the structure of the deterministic problem is fully preserved. For the case of continuous size of equipments, an efficient global optimization procedure is proposed, whereas for the case of discrete equipment sizes the algorithm reduces to the solution of a mixed integer linear programming problem. For short term production planning and long-range planning problems including capacity expansion options, the application of the proposed approach results in the optimal production plan (i. e. process utilization levels, purchases and sales of materials) and/or an optimal capacity expansion policy that maximize an expected profit and ensure an optimal level of future feasibility. Finally, an attempt to address the question of the future "value" of uncertainty is presented based on the concept of value of perfect information. It is shown that the proposed algorithmic developments can be effectively extended to include both the solution of the here-and-now and the wait-and-see models in order to analyze and integrate the

The ultimate goal in the manufacturing of a part is to achieve an economic production plan with precision and accuracy in the first attempt at machining. A physics-based comprehensive modeling of the machining processes is a fundamental requirement in identifying optimal cutting conditions which result in high productivity rates without violating accuracy throughout the part production process. This thesis presents generalized virtual simulation and optimization strategies to predict and optimize performance of milling processes up to 3-axis. Computationally efficient mathematical models are introduced to predict milling process state variables such as chip load, force, torque, and cutting edge engagement at discrete cutter locations. Process states are expressed explicitly as a function of helical cutting edge - part engagement, cutting coefficient and feedrate. Cutters with arbitrary geometries are modeled parametrically, and the intersection of helical cutting edges with workpiece features are evaluated either analytically or numerically depending on geometric complexity. The dynamics of generalized milling operations are modeled and the stability of the process is predicted using both time and frequency domain based models. These algorithms enable rapid simulation of milling operations in a virtual environment as the part features vary. In an effort to reduce machining time, a constraint-based optimization scheme is proposed to maximize the material removal rate by optimally selecting the depth of cut, width of cut, spindle speed and feedrate. A variety of user defined constraints such as maximum tool deflection, torque/power demand, and chatter stability are taken into consideration. Two alternative optimization strategies are presented: pre-process optimization provides allowable depth and width of cut during part programming at the computer aided manufacturing stage using chatter constraint, whereas the post-process optimization tunes only feedrate and spindle speed of an existing part program to maximize productivity without violating physical constraints of the process. Optimized feedrates are filtered by considering machine tool axes limitations and the algorithms are tested in machining various industrial parts. The thesis contributed to the development of a novel 3-axis Virtual Milling System that has been deployed to the manufacturing industry.

Microspheres are spherically shaped particles within the size range of 1-1000 μm in diameter. Due to the their small size and round shape, microspheres show many advantages in various applications such as pharmaceuticals, composites and coatings. The microspheres can be customized to fit a specific application and are manufactured in various forms such as solid, hollow and encapsulating. Encapsulating cellulose microspheres have been produced in this project by the emulsionsolvent evaporation technique. The purpose of this study was to further investigate the possibility of producing encapsulating microspheres with a size range of 10-50 μm that will have a high encapsulation. A second purpose of this study was optimizing the emulsifier system for the preparation of these spheres. This has been accomplished by varying several process parameters such as type of emulsifiers and solvents to study the effect on morphology and encapsulation efficiency. The analyses of the spheres were performed with optical microscopy, thermal gravimetric analyzer (TGA) and scanning electron microscopy (SEM). The emulsifier type and concentration affected the encapsulation and size distribution but had no direct effect on the internal and external structure, which was multi-cellular and porous, respectively. The highest encapsulation in relation to average size was obtained with 0.1 v/v- % of the emulsifier mixture Emulsifier 1 (E1)/Emulsifier 2 (E2) (70/30 %). The solvent used to dissolve the polymer had a direct effect on encapsulation, a combination of Solvent 2 (S2) and Solvent 1 (S1) proved best for the three tested cellulose derivatives with low, medium and high number average molecular weight. The solvent also had an effect on the internal structure of the microspheres, becoming more core-shell when using the S1/S2 combination.

碩士<br>龍華科技大學<br>電子工程系碩士班<br>104<br>SMT process comprises three main manufacturing processes: 1.solder paste printing 2.surface mount /placement 3. reflow. Reflow process is one of the most key points to influence the quality of PCBA soldering, and soldering condition directly affect the electronic product functionality, reliability and security. Reflow process contains 4 parts, 1.Preheater zone; 2.Soak Zone; 3.Reflow Zone; 4.Cooling Zone. Each step has its own temperature and time (which is called Reflow Profile) and this profile directly affect the electronic product functionality, reliability and security. While the profile curve can be controlled effective, some potential quality issues, such as Sn particle, tomb stone, chip rotate, crack, flux inactive, etc may reduce. We will discuss the model (YX-LFHACRF) parameters of 2 steps during reflow process in this paper, such as peak temperature, preheat time, in order to enhance strength and reliability of soldering.

碩士<br>國立高雄第一科技大學<br>機械與自動化工程研究所<br>103<br>LED Bulb for today&apos;&apos;s popular and emerging industries, originally mainly used on some of the lighting industry, the industry has now started production in Minsheng use, LED bulb compared to the average energy saving bulbs, whether it is life or saving aspects are more than 30 times, more environmentally friendly and less polluting, but due to production and assembly is required when more than manual assembly, manual assembly work a lot of orders for too long, resulting in high costs, leading to people&apos;&apos;s livelihood with LED bulb prices have been high , resulting in sales has been unable to improve and spread, LED ball bulbs require automated assembly equipment, in order to reduce the cost and time.

碩士<br>樹德科技大學<br>經營管理研究所<br>93<br>Following scientific and technological progress, the requirements of electronic products become increasingly thinner, lighter, smaller and functionally more powerful models, such as cell phones, laptop computers, PDAs, digital cameras and other gadgets are sought after. In view of this perspective, electronics manufacturers have been developing more stable production methods that assure greater stability, which in turn promotes the development of better technologies for printed circuits board assembly (PCBA). Of the latter, the key lies in the development of the Surface Mount Technology (SMT) assembly process. Stencil printing is one of the most important processes in SMT assembly. An average 60% of soldering defects are attributed to inadequate stencil printing parameter settings. Today, there are no standard parameter sets for stencil printing in the electronic industry. The manufacturing process of new products always requires trial printing before production launch, through which the printing parameters were obtained by trial and error approach. In this study, two optimization models of stencil printing parameters were developed. A fractional factorial experiment design was conducted for collecting structured data to closely investigate the relationships of inputs and outputs and followed by using Response Surface Method (RSM) and Genetics algorithms (GAs) to optimize the given process. Finally, two optimized parameter sets obtained and compared with the empirical SPC data for performance assessments. Results show that the parameter combinations optimized by GAs is superior to RSM. The findings can further provide electronic manufacturers to speed up line setup procedure and improve soldering quality.

博士<br>國立交通大學<br>工業工程與管理系所<br>98<br>Taguchi’s parameter design is a powerful tool to improve product performance, and widely applied in industry. It is the largest contribution to quality methodology that Taguchi has made. However, Taguchi’s parameter design approach has limitations in practice, it can not obtain real optimal parameter combinations when the parameters are in continuous values, and only identify the most favorable solution among the pre-specified control factor levels. In a multi-responses system, the responses need to be optimized simultaneously. On the other hand, the sensitivity measure and variability measure need to be optimized simultaneously in a dynamic system, but in practice, these objectives are often conflict. In this study, we propose integrating a hierarchical genetic algorithm (HGA) based neural network and a multiple objective evolutionary algorithm (MOEA) to optimize the parameter design problem. Different sets of data either from other researchers' works or case study conducted in this research have been used to demonstrate the effectiveness of this proposed approach

Thesis (Ph. D.)--University of Wisconsin--Madison, 1993.<br>Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 140-148).

碩士<br>國立交通大學<br>工業工程與管理系所<br>97<br>In recent years, the key reasons for the success in software industry are the capability of managing software development process in addition to the use of new technology. In order to improve the software development process (SDP), Capability Maturity Model Integration (CMMI) is widely adopted by the software companies all over the world. The staged approach of CMMI yields appraisal results as one of five maturity levels. Many organizations have conducted the appraisal of maturity level 2 or 3. However, when software organizations continuously enhance their software process maturity to maturity level 4 or 5, most of them are confronted with some difficulties. Many studies proposed methods, including Statistical Process Control (SPC), prediction models and some quantitative simulation methods, to help software organizations to meet the requirements of maturity level 4 or 5. However, some of these quantitative methods, such as stochastic optimization modeling (SOM), are too complicated for software engineers or managers to learn and employ. Another drawback is that adopting these methods is too time-consuming. To simplify the process of optimizing the single performance-indicator, this study utilizes the analysis of variance (ANOVA) to determine the best option of each sub-process. The proposed method can not only achieve the effect as SOM but also save a lot of time or effort as compared with SOM. In addition, this study utilizes the multivariate analysis of variance (MANOVA) to optimize multi-performance-indicator simultaneously and determine the best option of each sub-process. Finally, a real case from a paper of SEI is utilized to demonstrate the effectiveness of the proposed procedure.

The dissertation deals with potential energetic saving in cow milk cooling. The theoretical part contains an information about cow milk and refrigeration systems for milk cooling. Measuring in laboratory conditions was performed with the aim to collect a sufficient quantity of measured data for the qualified application of flat-plate coolers in measuring under real operating conditions. The practical part measuring in real operating conditions was implement in a farm. The practical part examines milk cooling using milk flow-through plate coolers and from the values obtained it formulates conclusions and recommendations for practice.

碩士<br>東海大學<br>化學工程學系<br>94<br>A large number of real-world problems require that decisions be made in the presence of uncertainty. Traditionally, the task of design and synthesis of chemical processing systems neglects influence of uncertainties (e.g., temperature and flowrate variations, stream composition changes, imprecise design data). In this work, modeling of optimization problems under uncertainty employs the method of classical stochastic programming and uses Hammersley sequence sampling technique to ensure uniform sampling in the uncertainty parameter space. Optimization under uncertainty is solved by simulated annealing and stochastic annealing, both of which have a tendency of reaching the global optimum. Two case studies have been conducted. In Case 1, process of benzene to cyclohexane is optimized based on a superstructure formulation, taking uncertainties such as temperature, flowrate and composition variations into consideration. It is essentially an MINLP problem. Comparison is made for the optimal process structures generated with and without uncertainties. Case 2 explores a separation design problem by considering uncertainties associated with dependent thermodynamic parameters. Also, confidence region is identified by the nonlinear least squares method. Overall, this study gives designers a new perspective in process design in the face of uncertainties.

碩士<br>國立高雄應用科技大學<br>電機工程系博碩士班<br>103<br>A wide variety of electronic components, protection during transport or use of is the use of carrier tape. Use tape carrier can be divided into two kinds of active components and passive components, the main use is in the packaging element, how to make element being the best protection lies in the design and manufacture of the carrier tape, allowing optimal space design element hosted, the element in the production and transportation can be the best protection. How to shorten the process test time, how to improve process yield, in order to meet customer requirements, so obtained in the limited time optimal process parameters is the primary objective. In this paper, the carrier tape process parameters optimized for the application of multi-objective research and explore examples of application Taguchi method to design experiments. Process carried out against non-performing ratio analysis, process temperature control machine is stable, temperature control of the manufacturing process to select four parameters, explore different control parameters and temperature impact on their production and size of the strip. Use Taguchi experimental method to explore the differences between portfolio yield optimization size and find a suitable combination with a way to optimize. Finally, the optimum parameters with the original parameters yield than the right, demonstrate the effectiveness of this article, but also make the process shorter test time, increase production yields. Keywords：Taguchi Method,Process Optimization

碩士<br>國立中央大學<br>機械工程學系在職專班<br>104<br>Centerless grinding process is widely used in producing the extra-smooth surface, particularly in the hard and brittle materials such as aluminum oxide (Al2O3), zirconium oxide (Zr2O3) and silicon carbide (SiC). The stability of the centerless grinding process is very sensitive to the set-up conditions due to the uniqueness of the work-holding system. Centerless grinding produces precision components with high productivity only when the set-up condition is optimally chosen .This thesis describes the effect of set-up conditions on the stability criteria of the centerless grinding system . Guidelines are proposed for determining proper set-up conditions to avoid spinners, chatter vibration and roundness problems. Finally, the optimum set-up condition based on experiments are proposed and the validation results are discussed.

碩士<br>中原大學<br>機械工程研究所<br>93<br>ABSTRACT In order to accommodate the market trend and satisfy the demand of consumable electronic product, the major design houses tend to design a chip with high density and multiple working capabilities. Relatively, to reduce the development time and resolve the delivery pressure coming from the customer, the foundries need to continuously promote their process technology to adopt these new products. Therefore, the foundries currently focus on the subject of finding the optimal process parameters quickly and efficiently. Recently, the orthogonal arrays and simple genetic algorithm (SGA) have been widely used to find the optimal parameters for a new developed process. Intelligent genetic algorithm (IGA) is an optimized algorithm, which closely combines the two totally different optimization mechanisms of orthogonal experimental design and SGA, and it also improves the “crossover operation” in the traditional SGA. In this research, we use orthogonal arrays (OAs) to train a neural network (NN), and then use this NN to create a Copper CMP process model. Finally, we combine IGA and this process model to find the global optimum, achieving the goal of optimization of parameter design, and also verifying the effectiveness of this method. Some controllable factors, such as polish pressure, polish speed, and polish time, are used to be the key optimal parameters of IGA. In the case of Cu film removal rate target 5500 Å, the data converge at the 30th generation, and finally a set of optimal parameters appears at the 96th generation. After applying those parameters to the real CMP tool, we get an average removal rate of 5567 Å, and a standard deviation of 24 Å. The result has approved that, comparing to the traditional Taguchi method, the approach in this study is able to get a set of optimized parameters with better accuracy and precision.

碩士<br>樹德科技大學<br>經營管理研究所<br>98<br>表面黏著(Surface Mount Technology, SMT)自動化生產技術之發展日趨完善，近乎所有消費性電子產品皆須藉由SMT 生產技術而產出，SMT 製程包含三個連續製造程序，(i)錫膏印刷(Stencil printing)、(ii)零件黏貼(Component placement)、及(iii)迴焊(Solder reflow)。其中迴焊為直接影響焊接品質之重要製程，迴焊過程中，藉由控制迴焊爐溫度曲線，使錫膏熔融後連接電子元件與PCB 進而形成焊點，迴焊溫度曲線控制是否得當影響焊點結構與其可靠度，今迴焊作業的輸入/輸出變數間關係仍尚未被完全理解。鑒於目前業界對迴焊製程參數組合並無一個最佳化標準可依循，於新產品生產或進行產品線更換作業時，根據工程師之實務經驗採取試誤法找尋最佳化迴焊溫度曲線，本研究重點於如何取得迴焊溫度曲線最佳參數，根據文獻及專家建議之輸出值與輸入值作為參數設定之關鍵，並配合實驗設計資料，作為實驗樣本，運用反應曲面與非線性規劃找尋最佳迴焊參數組合，找出最佳溫度曲線，使製程工程師可經由迴焊製程最佳參數，用以快速執行與管控迴焊製程。