A Decision-Information-Synchronisation perspective on the performance of FMS

The performance of a Flexible Manufacturing System (FMS) largely depends on how the control system can control the flow of entities in the system. The control system takes control decisions based on the information provided as an input to the decision-making process. Therefore, it is important that the decision-making process and information systems operate in a synchronised manner with respect to the FMS characteristics. This can also be referred to as a Decision-Information-Synchronisation (DIS) operating zone implemented in the control system. To study the DIS in the present research, three types of visibility for decision-makers in FMS shop-floor control have been identified: (1) no local visibility, (2) physical local visibility and (3) physical and information local visibility of decision-maker/operator. These alternative visibilities and automation levels of decision and information system provide the hybrid environments of FMSs control. The current paper presents an approach to identify the DIS operating zone of FMS with suitable visibility of decision-maker and automation level. Simulation results show that under non-real-time control (low automation level in decision and information system) with physical local visibility, the FMS system performs comparable with the real-time control (high automation level in decision and information system) when routing flexibility levels are presented. Under the current global competitive environment, this study helps industrial managers determine a suitable level of visibility and automation in planning an FMS control system in order to obtain the desired performance at the lower cost.     

Provident decision making by considering dynamic and fuzzy environment for FMS evaluation

When evaluating complexity, cost and risk increase, it is difficult to make a proper decision. In such situations it is necessary to develop a model which simulates a decision maker's mind and consider both a dynamic and a fuzzy environment. In this study future oriented indices are presented which enable us to consider the effect of future changes in the index value during the decision making process. These future oriented indices are named provident indices. Also in this study to effectively integrate these multiple criteria into the decision making process, based on the analysis of the decision situation in such assessments, a suitable concept is selected. This method is based on the preference ranking organisation method for enrichment evaluations (PROMETHEE) which brings together flexibility and simplicity for the user and is therefore chosen for the enhancement towards the evaluation of fuzzy data on preferences, scores and weights. The model developed to investigate these impacts cannot perfectly reproduce all the events of the real system, but it can consider a fair number of elements of variability, which should be identified and analysed by considering present conditions and prediction about criteria values in future periods. Such a model may provide solutions with a high degree of robustness and reliability, comparable with those obtained by direct experimentation, but with a low computational cost. The uniqueness of this paper lies in two important areas: first, the incorporation of variability fuzzy and provident measures in the performance of alternatives into the decision making process; and second, is in the application of fuzzy PROMETHEE that provides the decision maker with effective alternative choices by identifying significant differences among alternatives and appropriate choices through considered future periods, and presents graphic aids for better interpretation of results. A comprehensive numerical example of a flexible manufacturing system (FMS) is provided to illustrate the results of the analysis. In a real-world manufacturing environment, the dynamics of an FMS and its stochastic characteristics require a specific approach for evaluation. This paper specifically focuses on FMSs due to the complexities involved in their proper evaluation that include factors such as high operational and managerial expertise in system implementation phases, high costs and risks. Due to these, evaluation, justification, and implementation of an FMS have been areas of major concern and importance for practitioners and researchers. In this case, various strategic, economic and operational criteria that envelop quantitative, qualitative, tangible, and intangible factors are considered.     

Multicriteria dynamic scheduling methodology for controlling a flexible manufacturing system

A methodology is presented for the dynamic scheduling of flexible manufacturing systems (FMSs). A two-level control hierarchy is suggested. The higher level is used for determining a dominant decision criterion and relevant scheduling rules, based on an analysis of the actual shop status. The lower level uses simulation for determining the best scheduling policy to be selected. Simulation is used to evaluate different control options, and once a control decision is made, it is operated in real time to serve as the FMS controller. The suggested scheduling and control scheme is being developed, implemented and tested in a physical computer integrated manufacturing (CIM)/FMS environment at the CIM and Robotics Lab of the Faculty of Industrial Engineering and Management, Technion. This will serve as a test-bed to study the performance of the FMS under different scheduling rules and control options, and to recommend the best combination of control policies and parameters for specific system conditions and global production objectives.     

Application of multiple objective optimization theory to a preliminary missile design study

In this large-scale project, the design tasks were divided into two parts which allowed for increased efficiency. The modelling and generation of optimal candiatte missile designs were separated from the preference-laden design selection process. A set of performance indices including range, cost, trajectory error, system susceptibility, and reliability were established as the system measures with which all the subsystems were subsequently optimized. A team of technical designers used computer-based submodels in the areas of propulsion, lifecycle cost, and system susceptibility along with analytical models in the areas of trajectory analysis and system reliability to construct a statespace model. The system statespace included a set of established constants, and it mathematically linked the various subsystems to the performance measures. This model was then nested inside a vector optimization algorithm on a digital computer. The output of this interactive computer program is a set of efficient or nondominated missile designs. Each design is defined by its set of state variables, and accompanied by a set of performance index scores and control variables which define its particular trajectory. These nondominated designs show explicitly the tradeoffs among the performance indices for the missile systems as one moves along the efficient frontier of designs. Additional sensitivity analysis is provided by the optimization software for each efficient design. The second phase of the design process consisted of identifying one missile design from the efficient set for further development. This identification process results from ranking of the efficient designs according to a scalar scoring function which relies on the decision maker's preferences.     

Experimental investigation of flexible manufacturing system scheduling decision rules

This paper reports the results of an experimental investigation of scheduling decision rules for a dedicated flexible manufacturing system. A simulation model of an existing flexible manufacturing system (FMS) comprised of 16 computer numerical controlled machines (CNC) was constructed using actual operation routings and machining times to evaluate the performance of various part loading and routing procedures. The results indicate that FMS performance is significantly affected by the choice of heuristic parts scheduling rules.     

A competitive neural network approach to multi-objective FMS scheduling

The main contribution of this paper is the development of a multi-objective FMS scheduler which is designed to maximally satisfy the desired values of multiple objectives set by the operator. For each production interval, a decision rule for each decision variable is chosen by the FMS scheduler. A competitive neural network is applied to present fast but good decision rules to the operator. A unique feature of the FMS scheduler is that the competitive neural network generates the next decision rules based on the current decision rules, system status and performance measures. A commercial FMS is simulated to prove the effectiveness of the FMS scheduler. The result shows that the FMS scheduler can successfully satisfy multiple objectives.     

The design and validation of a digital simulation model for job shop control decision making

A previous paper (Browne et al. 1981) identified the decision making problems associated with job shop control and presented an objective function for measuring its performance. Given that definition of job shop control and cost-based objective function, simulation modelling offers the best prospect of a solution of the problem of providing a management tool to aid in the decision making associated with job shop control. This paper provides a detailed analysis of the design of such a model. The model, written in the GASP fV simulation language and running on a CDC 7600 computer, is based on the job shop of a major machine tool manufacturer and has been validated against actual job shop performance.     

A reliable decision support system for fresh food supply chain management

The paper proposes a decision support system (DSS) for the supply chain of packaged fresh and highly perishable products. The DSS combines a unique tool for sales forecasting with order planning which includes an individual model selection system equipped with ARIMA, ARIMAX and transfer function forecasting model families, the latter two accounting for the impact of prices. Forecasting model parameters are chosen via two alternative tuning algorithms: a two-step statistical analysis, and a sequential parameter optimisation framework for automatic parameter tuning. The DSS selects the model to apply according to user-defined performance criteria. Then, it considers sales forecasting as a proxy of expected demand and uses it as input for a multi-objective optimisation algorithm that defines a set of non-dominated order proposals with respect to outdating, shortage, freshness of products and residual stock. A set of real data and a benchmark – based on the methods already in use – are employed to evaluate the performance of the proposed DSS. The analysis of different configurations shows that the DSS is suitable for the problem under investigation; in particular, the DSS ensures acceptable forecasting errors and proper computational effort, providing order plans with associated satisfactory performances.     

Performance evaluation of tandem and conventional AGV systems using generalized stochastic Petri nets

This paper investigates the different policies and concepts followed in the traffic management of automated guided vehicle (AGV) systems, and develops the controls for automatically eliminating potential vehicle conflicts in an AGV system. The planning of the AGV system is performed in such a way that there are no conflicts or deadlocks for the vehicles using stochastic Petri nets (SPNs). The major effort is devoted to determining the benefits of the tandem AGV control in comparison with the conventional AGV control method. SPNs have been used to model the different designs of flexible manufacturing systems (FMSs) and with different policies for the movement of material, vehicle path control, inventory planning and tool control. The SPN model is solved and the performance of the system can be evaluated. In this study, the effort is directed to model an FMS with two different types of AGV traffic management methods, namely the conventional and tandem AGV control. A SPN program is used which takes the FMS Petri net model as the input and evaluates the different properties of the Petri net. Finally the performance measures are obtained, which helps in evaluating and comparing the two different AGV traffic management methods.     

DECISION INTEGRATION FUNDAMENTALS IN DISTRIBUTED MANUFACTURING TOPOLOGIES

Advances in control, communications, computer science and engineering have made it possible to design and implement large scale systems, where the decision making, control and information processing are distributed. This research effort attempts to establish the theoretical foundation of operational decision integration for such systems. Decision integration is a method to improve the quality of decision making. The basic elements of the integration process are defined. A simple distributed hypothesis testing model is employed to demonstrate that properly designed integration always improves the quality of the decisions. The problem of organizing decision making agents into architectures of integration (parallel versus hierarchical) is addressed. Several elementary decision architectures for small organizations are analyzed, and their performance is compared. The results are also extended for the case of flexible architectures with adaptive topology. The implications of integration are discussed with respect to the overall performance of an organization.     

On the feasibility of sequence-dependent economic lot scheduling problem

Most of the literature dealing with the determination of cyclic part input sequences in a flexible flow system is restricted in that it only searches for input sequences that are permutations of the minimal part set (MPS). This study is unique in that it investigates input sequences generated by integer programming (IP) formulations that balance or unbalance machine workloads to help maximize overall machine utilization (Stecke 1992). Also, this study integrates the input sequence determination decision with the part mix ratio determination, within the overall framework of a flexible approach to FMS operation over time. A simulation model of a flexible flow system was designed to study the effects on overall machine utilizations caused by utilizing alternative part mix ratios to help determine input sequences. The procedures used to determine the part mix ratios include IP formulations and those that are generated randomly, including the MPS mix ratios. Three different experimental settings are used to test these effects as well as (I) the robustness of the part input sequences that can be derived from the IP generated mix ratios, and (2) the relative importance of the part mix ratio decision in relation to the part input sequence determination. A new FMS physical design that can also be easily modelled to capture look-ahead capability proved to be simple and effective. Several significant conclusions regarding part mix ratios, pan input sequences, and look-ahead capability are revealed. These include: (1) the determination of the part mix ratios proved to be more significant in improving FMS performance than the determination of part input sequences; (2) the robust nature of the IP formulations was demonstrated; and (3) look-ahead capability provides equally high overall machine utilizations at lower levels of work-in-process. Future research areas are presented that would help validate and extend the observations found in this study.     

Development of a simulation-based optimisation for controlling operation allocation and material handling equipment selection in FMS

Flexible manufacturing system (FMS) is described as a set of computerised numerical controlled machines, input–output buffers interconnected by automated material handling devices. This paper develops a bi-objective operation allocation and material handling equipment selection problem in FMS with the aim of minimising the machine operation, material handling and machine setup costs and maximising the machine utilisation. The proposed model is solved by a modified chaotic ant swarm simulation based optimisation (CAS²O) while applying pre-selection and discrete recombination operators is surveyed a capable method to simulate different experiments of FMS problems. A test problem is selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method to solve the FMS scheduling problem.     

Distance-based fuzzy MCDM approach for evaluating flexible manufacturing system alternatives

Considering the high required capital outlay and moderate risk of a flexible manufacturing system (FMS) investment, economic justification techniques are insufficient by themselves since they cannot cope with the benefits such as flexibility and enhanced quality offered by advanced manufacturing technologies. A robust decision-making procedure for evaluating FMS requires the consideration of both economic and strategic investment measures. A distance-based fuzzy multicriteria decision-making (MCDM) framework based on the concepts of ideal and anti-ideal solutions is presented for the selection of an FMS from a set of mutually exclusive alternatives. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The multicriteria decision approach presented here enables us to incorporate data in the forms of linguistic variables, triangular fuzzy numbers and crisp numbers into the evaluation process of FMS alternatives. Linguistic variables are also used to indicate the criteria's importance weights assigned by the decisionmakers. A comprehensive example illustrates the application of the multicriteria decision analysis.     

Effects of flexibility and scheduling decisions on the performance of an FMS: simulation modelling and analysis

This paper focuses on a simulation-based experimental study of the effects of routing flexibility, sequencing flexibility, and part sequencing rules on the performance of a typical FMS. Three routing flexibility levels, five sequencing flexibility levels, and four scheduling rules for part sequencing decision are considered for detailed investigation. The system work load characterised by the mean interarrival time of parts has been set at different levels. The performance of the FMS is evaluated using various measures related to flow time and tardiness of parts. The simulation results are subjected to statistical analysis. Multiple regression-based metamodels have been developed using the simulation results. The analyses of results reveal that deterioration in system performance can be minimised substantially by incorporating either routing flexibility or sequencing flexibility or both. However, the benefits of either of these flexibilities diminish at higher flexibility levels. When flexibility exists, part sequencing rules such as the earliest due date and earliest operation due date provide a better performance for all the measures.     

Performance-based dynamic scheduling model for flexible manufacturing systems

A performance-based dynamic scheduling model for random flexible manufacturing systems (FMSs) is presented. The model is built on the mathematical background of supervisory control theory of discrete event systems. The dynamic FMS scheduling is based on the optimization of desired performance measures. A control theory-based system representation is coupled with a goal programming-based multi-criteria dynamic scheduling algorithm. An effectiveness function, representing a performance index, is formulated to enumerate the possible outputs of future schedules. Short-term job scheduling and dispatching decisions are made based on the values obtained by optimizing the effectiveness function. Preventive actions are taken to reduce the difference between actual and desired target values. To analyse the real-time performance of the proposed model, a software environment that included various Visual Basic Application® modules, simulation package Arena®, and Microsoft Access® database was developed. The experimentation was conducted (a) to determine the optimum look-ahead horizons for the proposed model and (b) to compare the model with conventional scheduling decision rules. The results showed that the proposed model outperformed well-known priority rules for most of the common performance measures.     

Performability of FMS based on stochastic process models

We address the design for reliability of complex systems, such as Flexible Manufacturing Systems (FMS), through mathematical modelling of the machine failure, spares inventory, and repair processes. The unique model allows separation of systems by Machine Part Type (MPT); thus, we can model an extremely complicated FMS through many simpler models. Our measure of system effectiveness is based on a performability measure that credits partial availability by the performance of the system in that state. By comparing performability measures, designers and managers can affect the system reliability. Examples demonstrate how to use these developments.     

FMS Designer: An expert system for flexible manufacturing system design

Implementation of flexible manufacturing technology in the batch manufacturing environment has created major problems for designers and engineers who are responsible for specification and design of flexible manufacturing systems (FMS). The FMS design task appears to be an excellent application for expert systems techniques. This paper describes current results of an ongoing research effort to develop an expert system which analyses the output from an FMS simulation model, determines whether operational and financial objectives are met, identifies design deficiencies or opportunities for improvement, and proposes designs which overcome deficiencies or exploit improvement opportunities. An overview of the FMS design expert system is given and a case study is presented to illustrate how the system operates. Areas for future research are also discussed.     

轴类零件工艺平面布置决策支持系统的研究

针对轴类零件工艺平面布置随机性强的问题，提出用矩阵来描述其布置和设计，解决了工艺平面布置决策支持系统（DSS）中信息描述困难这一关键问题。决策过程中，输入本企业当前有关数据，通过人机协调和动态管理，使决策更加切合企业实际情况从而避免投资浪费和风险。该系统（DSS）为制造企业技术改造投资、工艺平面布置设计和决策提供了有力的帮助。     

An analytical approach to quantitative effect estimation of operation advisory system based on human cognitive process using the Bayesian belief network

The design of instrumentation and control (I&C) systems for nuclear power plants (NPPs) is rapidly moving towards fully digital I&C systems and is trending towards the introduction of modern computer techniques into the design of advanced main control rooms (MCRs) of NPPs. In the design of advanced MCRs, human–machine interfaces have improved and various types of decision support systems have been developed. It is important to design highly reliable decision support systems in order to adapt them in actual NPPs. In addition, to evaluate decision support systems in order to validate their efficiency is as important as to design highly reliable decision support systems. In this paper, an operation advisory system based on the human cognitive process is evaluated in order to estimate its effect. The Bayesian belief network model is used in the evaluation of the target system, and a model is constructed based on human reliability analysis event trees. In the evaluation results, a target system based on the operator's cognitive process showed better performance compared to independent decision support systems.     

A methodology for planning and controlling workload in a job-shop: a four-way decision-making problem

There has been extensive research on workload and input–output control with the objective of improving manufacturing operations in job-shops. In this paper, a multiple decision-making scheme is proposed to plan and control operations in a general job-shop, and to improve delivery and workload related performance measures. The job-shop characteristics reinforce the need for designing a global system that controls both the jobs entering (order acceptance, due date setting and job release) and the work-in-process (dispatching), leading to an improvement of operational measures. Previous research has concentrated on scheduling a set of orders through the shop floor, according to some decision mechanism, in order to optimise some measure of performance (usually total lead time). This means that, since only a part of the decision-making system is being optimised, the resulting decision may be sub-optimal. In this paper it is shown that the performance of the different decision rules changes when they are considered simultaneously. Hence, a higher level approach, where the four decisions (order acceptance, due date setting, job release and dispatching) are considered at the same time, should be adopted to improve job-shop operational performance.