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Optimization of Product Flows in Flexible Manufacturing Systems Optimization of product flows in flexible manufacturing systems Citation for published version (APA): van Pinxten, J. H. H. (2018). Optimization of product flows in flexible manufacturing systems. Technische Universiteit Eindhoven. Document status and date: Published: 20/12/2018 Document Version: Publisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers) Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement: www.tue.nl/taverne Take down policy If you believe that this document breaches copyright please contact us at: [email protected] providing details and we will investigate your claim. Download date: 01. Oct. 2021 OWS SYSTEMS OF TION CTURING A PRODUCT FL OPTIMIZA IN FLEXIBLE MANUF AN PINXTEN V JOOST Optimization of Product Flows in Flexible Manufacturing Systems PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Technische Universiteit Eindhoven, op gezag van de rector magnificus prof.dr.ir. F.P.T. Baaijens, voor een commissie aangewezen door het College voor Promoties, in het openbaar te verdedigen op donderdag 20 december 2018 om 13:30 uur door Joost Hendrikus Hubertus van Pinxten geboren te Sint-Michielsgestel Dit proefschrift is goedgekeurd door de promotor en de samenstelling van de pro- motiecommissie is als volgt: voorzitter: prof.dr.ir. J.H. Blom 1e promotor: prof.dr.ir. T. Basten co-promotor: dr.ir. M.C.W. Geilen leden: prof.dr. Sebastian Engell (Technische Universität Dortmund) prof.dr. Frits Vaandrager (Radboud Universiteit Nijmegen) prof.dr.ir. Jeroen Voeten dr. Lou Somers Het onderzoek dat in dit proefschrift wordt beschreven is uitgevoerd in overeenstemming met de TU/e Gedragscode Wetenschapsbeoefening. Optimization of Product Flows in Flexible Manufacturing Systems J.H.H. van Pinxten Advanced School for Computing and Imaging This work was carried out in the ASCI graduate school. ASCI dissertation series number 402. This work is part of the research program Integrated Scheduling and Control with project number 12693, which is (partly) financed by the Netherlands Organisation for Scientific Research (NWO). Copyright © 2018, J.H.H. van Pinxten. All rights reserved. Reproduction in part or in whole is prohibited with- out the written consent of the copyright owner. Printed by Proefschriftmaken, The Netherlands A catalogue record is available from the Eindhoven University of Tech- nology Library. ISBN 978-94-6380-165-2 To my family and our purrito’s. Summary Optimization of Product Flows in Flexible Manufacturing Systems Wafer scanners, robotic assembly lines, and industrial printers are examples of flexible manufacturing systems (FMSs) that manufacture customized products. Wafer scanners expose silicon wafers with UV-light in a process to create com- puter chips, and industrial printers transfer digital images onto sheets of paper. Each product may have different requirements or characteristics, which can lead to different timing constraints between operations. The productivity of FMSs is limited by cyber constraints, such as the computation time of an on-line schedul- ing algorithm, as well as physical constraints, such as limitations on the movement of a product. The interaction between components in FMSs as well as their pro- ductivity requirements are ever increasing. In this thesis, we provide techniques to perform on-line scheduling of the product flows of such cyber-physical FMSs, and to analyse the impact of system design parameters on total system performance. FMSs can take many forms. We focus on scheduling algorithms for re-entrant FMSs, i.e., where the product re-enters one of the machines. Such a use case is found in industrial printing, where a sheet (i.e., the product) needs to be printed on both sides, by passing through an image transfer station twice. The media types and output order of the sheets are determined by the customer, and are not al- lowed to be changed. After processing a sheet, the image transfer station may need to be reconfigured before it can process the next sheet. The reconfiguration times typically depend on the differences in length, thickness, coating, and other me- dia characteristics. The characteristics for a particular product, and therefore their timing requirements, are known only moments before the FMS must receive the processing instructions. Therefore, a scheduler must quickly calculate efficient timing instructions for each operation. The challenge is to merge the streams of unprinted sheets and re-entering printed sheets without collisions and without violating reconfiguration times, while optimizing the performance of the system. The sequence of the products at the image transfer station plays an important role in the performance of industrial printers, since it directly impacts the reconfigu- ration times between products. The performance is therefore determined by the interplay of user input, the physical parameters of the system components, and the scheduling decisions. vi First, we present an efficient on-line sheet scheduling algorithm for indus- trial printers. The problem is modelled using a re-entrant flow shop with set-up times, due dates, and fixed output order. Given a particular sequence of prod- ucts (i.e., a print job), the sheet scheduling algorithm determines a feasible and efficient sequence of operations at the re-entrant machine (i.e., the image trans- fer station). The timing instructions for each of the operations on the sheets can then be efficiently found. Our heuristic algorithm uses multi-objective optimiza- tion to explore intermediate sequencing options without performing backtracking. The heuristic leverages several properties of the scheduling problem, such as the output ordering of the sheets and limitations on the number of products that are partially processed. For the type of FMS considered, the output order of products within a batch (e.g., a print job is a batch of sheets) is fixed, but the batches still need to be ordered. The second contribution is a scheduling heuristic that determines the orders of batches and selects system settings for each batch, such that Pareto-optimal productivity and quality trade-offs are found. Optimizing input order is particu- larly relevant for FMSs that may need reconfiguration between different products, such as industrial printers. The problem is modelled as a Multi-objective Gener- alized Traveling Salesman Problem (MOGTSP) and the ordering algorithm is an on-line, multi-objective heuristic that yields good results in less computation time than the state-of-the-art approaches for MOGTSP. Third, we contribute a parametric critical path analysis for design-time ana- lysis. During the design phase, a designer needs to create a physical layout that realizes a particular topology, i.e., a set of machines and their interrelations. Such a layout is constrained by limitations from many different domains. Constraints may, for example, come from minimal and maximal heating times, minimal seg- ment lengths, or maximal velocities. The designer needs to choose a realization that simultaneously optimizes the total system behaviour and cost. Design pa- rameters such as segment length or travelling velocity directly influence the total system behaviour, as e.g. processing a product becomes faster or slower. Our para- metric critical path analysis identifies relationships between (physical) parameters and the productivity of an FMS. The scheduling graphs used in the sheet schedul- ing heuristic are annotated with affine expressions that relate timing constraints to design parameters. The analysis identifies bottlenecks in the productivity of an FMS in terms of affine expressions for different sets of parameter combinations. This analysis enables designers to identify how productivity depends on combina- tions of parameters. As a fourth contribution, we present an algorithm that determines the impact of certain parameters on scheduling. Changes in the parameters may lead to se- lecting different scheduling choices, and therefore creating different schedules. We show that for some classes of schedulers it is possible to retrieve information about which scheduling decisions are chosen for different parameter
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