Scheduling of non-repetitive lean manufacturing systems under uncertainty using intelligent agent simulation

World-class manufacturing paradigms emerge from specific types of manufacturing systems with which they remain associated until they are obsolete. Since its introduction the lean paradigm is almost exclusively implemented in repetitive manufacturing systems employing flow-shop layout configurations. Due to its inherent complexity and combinatorial nature, scheduling is one application domain whereby the implementation of manufacturing philosophies and best practices is particularly challenging. The study of the limited reported attempts to extend leanness into the scheduling of non-repetitive manufacturing systems with functional shop-floor configurations confirms that these works have adopted a similar approach which aims to transform the system mainly through reconfiguration in order to increase the degree of manufacturing repetitiveness and thus facilitate the adoption of leanness. This research proposes the use of leading edge intelligent agent simulation to extend the lean principles and techniques to the scheduling of non-repetitive production environments with functional layouts and no prior reconfiguration of any form. The simulated system is a dynamic job-shop with stochastic order arrivals and processing times operating under a variety of dispatching rules. The modelled job-shop is subject to uncertainty expressed in the form of high priority orders unexpectedly arriving at the system, order cancellations and machine breakdowns. The effect of the various forms of the stochastic disruptions considered in this study on system performance prior and post the introduction of leanness is analysed in terms of a number of time, due date and work-in-progress related performance metrics

Application of lean scheduling and production control in non-repetitive manufacturing systems using intelligent agent decision support

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Lean Manufacturing (LM) is widely accepted as a world-class manufacturing paradigm, its currency and superiority are manifested in numerous recent success stories. Most lean tools including Just-in-Time (JIT) were designed for repetitive serial production systems. This resulted in a substantial stream of research which dismissed a priori the suitability of LM for non-repetitive non-serial job-shops. The extension of LM into non-repetitive production systems is opposed on the basis of the sheer complexity of applying JIT pull production control in non-repetitive systems fabricating a high variety of products. However, the application of LM in job-shops is not unexplored. Studies proposing the extension of leanness into non-repetitive production systems have promoted the modification of pull control mechanisms or reconfiguration of job-shops into cellular manufacturing systems. This thesis sought to address the shortcomings of the aforementioned approaches. The contribution of this thesis to knowledge in the field of production and operations management is threefold: Firstly, a Multi-Agent System (MAS) is designed to directly apply pull production control to a good approximation of a real-life job-shop. The scale and complexity of the developed MAS prove that the application of pull production control in non-repetitive manufacturing systems is challenging, perplex and laborious. Secondly, the thesis examines three pull production control mechanisms namely, Kanban, Base Stock and Constant Work-in-Process (CONWIP) which it enhances so as to prevent system deadlocks, an issue largely unaddressed in the relevant literature. Having successfully tested the transferability of pull production control to non-repetitive manufacturing, the third contribution of this thesis is that it uses experimental and empirical data to examine the impact of pull production control on job-shop performance. The thesis identifies issues resulting from the application of pull control in job-shops which have implications for industry practice and concludes by outlining further research that can be undertaken in this direction

Evaluation of different dispatching rules in computer integrated manufacturing using design of experiment techniques

This research is based on the study of process planning and scheduling in job shop flexible manufacturing systems. This project need to evaluate planning algorithms, determine appropriate algorithms and suggest better algorithm as a tool to optimize the process planning. Extensive computational experiments are carried out to verify the efficiency of our algorithm using OpenCIM software. By using the OpenCIM simulation software, the evalution of planning algorithms were carried out base on different scheduling algorithms such as First In First Out (FIFO), Shortest Processing Time (SPT), and Maximum Priority. The target of this study is to evaluate the performance of selected dispatching rules for different operation on the existing Computer Integrated Manufacturing (CIM) facility using a simulation model against different performance measures and to compare the results with the literature. Three factors with three levels of severity along with 3 different scheduling dispatching rules, a 3 x 3 x 3 = 27 full factorial Design of Experiment (DOE) set-up were used to evaluated the performance of the system under study. Analysis of variance (AVONA) was used to identify the interactions between factors. Three performance measures, Total Run Time, Maximum Queue Length and Machine Efficiency were used in the experiments. The system performance depended on Machine Efficiency when the number of released parts is maximum and the number of priority is minimum. Furthermore, considering the maximum queue length, the system performs much better when the selected dispatching rule is either MAX PRIORITY or SPT with number of priority is one and number of part release is eight. The system’s total run time performs markedly better when the number of released parts is set at eight or higher. It was concluded that the overall best simple dispatching rules among all other simple rules in order of their performance are Shortest Processing Time (SPT), Maximum Priority, First In First Out (FIFO)

Decentralized Scheduling of Discrete Production Systems with Limited Buffers

Die Steuerung der Produktion ist eine der Kernaufgaben eines jeden produzierenden Unternehmens. Sie ist insbesondere wichtig, um auf die Anforderungen des Marktes und damit auf die Wünsche der Kunden reagieren zu können. Aktuelle Trends im Markt führen dabei zu einer hochindividualisierten Produktion bei gleichzeitiger Erhöhung der produzierten Stückzahlen. Eine Konsequenz daraus ist, dass Unternehmen über flexiblere und agilere Produktionssysteme verfügen müssen, um auf die sich ständig ändernden Kundenwünsche reagieren zu können. Da starre Fertigungslinien nicht mehr geeignet sind, werden zunehmend komplexere Strukturen wie die der Werkstattfertigung oder Matrixproduktion eingesetzt. Hierfür werden geeignete Steuerungsmethoden für die Produktion benötigt. Diese Arbeit beschäftigt sich mit eben jenen Steuerungsmethoden, genauer gesagt Methoden zur Planung von Produktionsaufträgen in diesen neuen Produktionssystemen. Zur Steuerung eignen sich echtzeitfähige und autonome Entscheidungssysteme, mit denen die Steuerung der neuen Organisationsstruktur der Produktion angepasst ist. Agentenbasierte Systeme bieten genau diese Eigenschaften und erlauben es, komplexe Planungsaufgaben in kleinere Teilprobleme zu zerlegen, die schneller und genauer gelöst werden können. Sie erfordern die Verfügbarkeit von Daten in Echtzeit und eine schnelle Kommunikation zwischen den Agenten, was heute dank der vierten industriellen Revolution zur Verfügung steht. Demgegenüber steht der erhöhte Koordinierungsbedarf, der in diesen Systemen beherrscht werden muss. Das Ziel dieser Arbeit ist es, einen dezentralen Produktionsplanungs-Algorithmus zu entwickeln, der in einem Multi-Agenten-System implementiert ist. Er berücksichtigt begrenzte Verfügbarkeit von Pufferplätzen an jedem Arbeitsplatz, ein Thema, das in der Literatur wenig erforscht ist. Der Algorithmus ist in einer flexiblen Werkstattfertigung anwendbar und zeigt eine große Zeiteffizienz bei der Einplanung größerer Mengen von Aufträgen. Um dieses Ziel zu erreichen, wird zunächst der Produktionsplanungs-Algorithmus ohne das Agentensystem entworfen. Er basiert auf der von \textcite{adams1988} veröffentlichten Shifting Bottleneck Heuristik. Da viele Änderungen notwendig sind, um die geforderten Eigenschaften berücksichtigen zu können, bleibt nur die grundlegende Vorgehensweise gleich, während alle Schritte der Heuristik von Grund auf neu modelliert werden. Anschließend wird ein Multi-Agenten-System entworfen, das die genannten Anforderungen abbildet und den Algorithmus zur Planung verwendet. In diesem System hat jeder Arbeitsplatz einen Arbeitsplatzagenten, der für die Planung und Steuerung seines zugeordneten Arbeitsplatzes zuständig ist, sowie einige zusätzliche Agenten für die Kommunikation, die Datenspeicherung und allgemeine Aufgaben. Der entworfene Algorithmus wird angepasst und in das Multi-Agenten-System implementiert. Da das System im praktischen Einsatz immer eine Lösung finden muss, stellen wir mögliche Fehlerfälle vor und wie mit ihnen umgegangen wird. Abschließend findet eine numerische Evaluierung mit zwei realen Produktionssystemen statt. Da sich diese Systeme in einem wichtigen Merkmal ähneln, werden weitere zufällig erzeugte Beispiele getestet und ausgewertet

E-POLCA to control multi-product, multi-machine job shops.

Control; Job; University; Research;

Scheduling of re-entrant flow shops

Bibliography: p. 34.Stephen C. Graves...[et al.

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Scheduling of a computer integrated manufacturing system: a simulation study

Purpose: The purpose of this paper is to study the effect of selected scheduling dispatching rules on the performance of an actual CIM system using different performance measures and to compare the results with the literature. Design/methodology/approach: To achieve this objective, a computer simulation model of the existing CIM system is developed to test the performance of different scheduling rules with respect to mean flow time, machine efficiency and total run time as performance measures. Findings: Results suggest that the system performs much better considering the machine efficiency when the initial number of parts released is maximum and the buffer size is minimum. Furthermore, considering the average flow time, the system performs much better when the selected dispatching rule is either Earliest Due Date (EDD) or Shortest Process Time (SPT) with buffer size of five and the initial number of parts released of eight. Research limitations/implications: In this research, some limitations are: a limited number of factors and levels were considered for the experiment set-up; however the flexibility of the model allows experimenting with additional factors and levels. In the simulation experiments of this research, three scheduling dispatching rules (First In/First Out (FIFO), EDD, SPT) were used. In future research, the effect of other dispatching rules on the system performance can be compared. Some assumptions can be relaxed in future work. Practical implications: This research helps to identify the potential effect of a selected number of dispatching rules and two other factors, the number of buffers and initial number of parts released, on the performance of the existing CIM systems with different part types where the machines are the major resource constraints. Originality/value: This research is among the few to study the effect of the dispatching rules on the performance of the CIM systems with use of terminating simulation analysis. This is also significant given the nature of the CIM systems that are mostly used to produce different parts in varying quantities and thus do not produce parts on a continuing basis. This research is amongst the first to study the combined effect of dispatching rule and the buffer size in the CIM systems where the job arrivals are predetermined and depend on the completion of the existing parts in the system. A description of how buffer size and initial part release is related to the performance of the CIM system under study for the studied priority dispatching rule is also provided.Peer Reviewe