Modelling flexible manufacturing systems through discrete event simulation

As customisation and product diversification are becoming standard, industry is looking for strategies to become more adaptable in responding to customer’s needs. Flexible manufacturing systems (FMS) provide a unique capability where there is a need to provide efficiency through production flexibility. Full potential of FMS development is difficult to achieve due to the variability of components within this complex manufacturing system. It has been recognised that there is a requirement for decision support tools to address different aspects of FMS development. Discrete event simulation (DES) is the most common tool used in manufacturing sector for solving complex problems. Through systematic literature review, the need for a conceptual framework for decision support in FMS using DES has been identified. Within this thesis, the conceptual framework (CF) for decision support for FMS using DES has been proposed. The CF is designed based on decision-making areas identified for FMS development in literature and through industry stakeholder feedback: set-up, flexibility and schedule configuration. The CF has been validated through four industrial simulation case studies developed as a part of implementation of a new FMS plant in automotive sector. The research focuses on: (1) a method for primary data collection for simulation validated through a case study of material handling robot behaviour in FMS; (2) an approach for evaluation of optimal production set-up for industrial FMS with DES; (3) a DES based approach for testing FMS flexibility levels; (4) an approach for testing scheduling in FMS with the use of DES. The study has supported the development of systematic approach for decision making in FMS development using DES. The approach provided tools for evidence based decision making in FMS

Performance Analysis of An Experimental Micro Flexible Manufacturing System (FMS)

Due to advanced technology, it is very important the performance of FMS for sensivity, production quality, repeatability and energy consumptions. Flexible manufacturing systems (FMSs) are the most automated and technologically sophisticated of the machine cell types used to implement cellular manufacturing. An FMS usually has multiple automated stations and is capable of variable routings among stations, while its flexibility allows it to operate as a mixed model system. The FMS concept integrates many of the advanced technologies that we met in previous units, including flexible automation, CNC machines, distributed computer control, and automated material handling and storage. In this experimental investigation, vibration and accelerations analysis of an experimental FMS with 5 degrees of freedom robot manipulator are presented. Firstly, experimental measurement of accelerations and vibrations are trained with a vibration measurement system and sensors. However, the process of production of part is a cycle of exact production time

フレキシブル生産セルの性能解析に関する研究

本文データは平成22年度国立国会図書館の学位論文(博士)のデジタル化実施により作成された画像ファイルを基にpdf変換したものである京都大学0048新制・課程博士博士(工学)甲第5117号工博第1238号新制||工||869(附属図書館)UT51-92-J164京都大学大学院工学研究科数理工学専攻(主査)教授 長谷川 利治, 教授 茨木 俊秀, 教授 片山 徹学位規則第4条第1項該当Doctor of EngineeringKyoto UniversityDFA

The investigation of the effect of scheduling rules on FMS performance

The application of Flexible Manufacturing Systems (FMSs) has an effect in competitiveness, not only of individual companies but of those countries whose manufactured exports play a significant part in their economy (Hartley, 1984). However, the increasing use of FM Ss to effectively provide customers with diversified products has created a significant set of operational challenges for managers (Mahmoodi et al., 1999). In more recent years therefore, there has been a concentration of effort on FMS scheduling without which the benefits of an FMS cannot be realized. The objective of the reported research is to investigate and extend the contribution which can be made to the FMS scheduling problem through the implementation of computer-based experiments that consider real-time situations. [Continues.

An investigation into tooling requirements and strategies for FMS operation

A study of the minimum tooling requirements and strategies for efficient operation of Flexible Manufacturing Systems, FMS's, in Assembly set Production, ASP, i.e production in sets of parts to completely assemble one or more product units, is presented in this research work. The main investigating tool is a simulation model. With this model the tool groups to be loaded into machines and fixtured pallet requirements were studied in conjunction with two scheduling rules. One is a FCFS rule and the other is a new rule, called MRPAS, which schedules work on the basis of the number of parts still unfinished belonging to an Assembly Set. The results of the research work show that ASP can be efficiently carried out in FMS's. However this requires that a good system set-up and adequate operating strategies are used. In particular appropriate tooling levels and good tooling configurations,TC's, i.e. combinations of tools in groups to be loaded into the machines, must be established to achieve high FMS performance. Tooling combination and duplication heuristic rules and the simulation model can be used for achieving this aim. The heuristic approach is shown to be necessary due to the impossibility, in a reasonable time, of evaluating the performance of FMS's under the large number of alternative tooling configurations which are possible. The level of fixtured pallets used can also have a great influence on system performance. Appropriate levels of these resources to operate FMS's for given TC's can be established using the methodology developed in this work. It is also important that good scheduling rules are used. In the cases studied, the MRPAS rule produces the best performance expressed as the combination of FMS utilization and production of complete assembly sets. Moreover a very small assembly set batch size, ASBS, i.e. number of AS released together into the FMS, is likely to be preferable. In the cases studied an ASBS of one performed best overall

Analusis and Modeling of Flexible Manufacturing System

Analysis and modeling of flexible manufacturing system (FMS) consists of scheduling of the system and optimization of FMS objectives. Flexible manufacturing system (FMS) scheduling problems become extremely complex when it comes to accommodate frequent variations in the part designs of incoming jobs. This research focuses on scheduling of variety of incoming jobs into the system efficiently and maximizing system utilization and throughput of system where machines are equipped with different tools and tool magazines but multiple machines can be assigned to single operation. Jobs have been scheduled according to shortest processing time (SPT) rule. Shortest processing time (SPT) scheduling rule is simple, fast, and generally a superior rule in terms of minimizing completion time through the system, minimizing the average number of jobs in the system, usually lower in-process inventories (less shop congestion) and downstream idle time (higher resource utilization). Simulation is better than experiment with the real world system because the system as yet does not exist and experimentation with the system is expensive, too time consuming, too dangerous. In this research, Taguchi philosophy and genetic algorithm have been used for optimization. Genetic algorithm (GA) approach is one of the most efficient algorithms that aim at converging and giving optimal solution in a shorter time. Therefore, in this work, a suitable fitness function is designed to generate optimum values of factors affecting FMS objectives (maximization of system utilization and maximization of throughput of system by Genetic Algorithm (GA) approach

Taxonomic classification of planning decisions in health care: a review of the state of the art in OR/MS

We provide a structured overview of the typical decisions to be made in resource capacity planning and control in health care, and a review of relevant OR/MS articles for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making

A study of the robustness of the group scheduling method using an emulation of a complex FMS

International audienceIn the field of predictive-reactive scheduling methods, group sequencing is reputed to be robust (in terms of uncertainties absorption) due to the flexibility it adds with regard to the sequence of operations. However, this assumption has been established on experiments made on simple theoretical examples. The aim of this paper is to carry out experimentation on a complex flexible manufacturing system in order to determine whether or not the flexibility of the group scheduling method can in fact absorb uncertainties. In the study, transportation times of parts between machines are considered as uncertain. Simulation studies have been designed in order to evaluate the relationship between flexibility and the ability to absorb uncertainties. Comparisons are made between schedules generated using the group sequencing method with different flexibility levels and a schedule with no flexibility. A last schedule takes into account uncertainties whereas schedules generated using the group sequencing method do not. As it is the best possible schedule, it provides a lower bound and enables to calculate the degradation of performance of calculated schedules. The results show that group sequencing perform very well, enabling the quality of the schedule to be improved, especially when the level of uncertainty of the problem increases. The results also show that flexibility is the key factor for robustness. The rise in the level of flexibility increases the robustness of the schedule towards the uncertainties

A multi-objective GA-based optimisation for holistic Manufacturing, transportation and Assembly of precast construction

Resource scheduling of construction proposals allows project managers to assess resource requirements, provide costs and analyse potential delays. The Manufacturing, transportation and Assembly (MtA) sectors of precast construction projects are strongly linked, but considered separately during the scheduling phase. However, it is important to evaluate the cost and time impacts of consequential decisions from manufacturing up to assembly. In this paper, a multi-objective Genetic Algorithm-based (GA-based) searching technique is proposed to solve unified MtA resource scheduling problems (which are equivalent to extended Flexible Job Shop Scheduling Problems). To the best of the authors' knowledge, this is the first time that a GA-based optimisation approach is applied to a holistic MtA problem with the aim of minimising time and cost while maximising safety. The model is evaluated and compared to other exact and non-exact models using instances from the literature and scenarios inspired from real precast constructions