Job Shop Control Research Articles

A Multi-Agent Model for Job-Shop Scheduling

The multi-agent paradigm is increasingly used in the analysis, modelling and design of complex systems with highly interacting components. In the framework provided by the generic prototyping approach, the paper presents a solution for the behaviour modelling of discrete event processes, where the decision-making capabilities of co-operating agents have to be emphasized. At the object level the DCPN (decision control Petri nets) formalism is proposed, while the coordinating mechanism at the system level has been developed according to the blackboard paradigm. The job-shop case study illustrates the approach. The conceptual model provided by this approach is being implemented in the MASIM (multi-agent simulator in manufacturing) module of a DSS for intelligent job-shop control.

Verification and validation issues in manufacturing models

Verification and validation are two techniques employed during the development of computer programs and the modelling of systems. Each of these techniques has a unique scope. Both techniques are an inherent part of the problem specification, program coding and the final implementation of the computer software in a real-life environment. The issues of verification and validation have become all the more critical as the scope of modern-day computer programs have evolved from data manipulation to performing cognitive tasks. This paper discusses the verification and validation issues in all three phases of software development. It introduces the basic definitions of models, verification and validation and goes on to describe their scope. Finally, the paper describes the lessons learnt from the validation of a Generalised Real-Time Job Shop Control System in a real-life manufacturing environment.

Hierarchical and dynamic production control in flexible manufacturing systems

Job shop control involves directing the flow of products through the manufacturing system. Centralized and decentralized approaches have been proposed. This paper introduces first a mix approach in the organization of real time control level in flexible manufacturing systems: a hierarchical organization permits coordination of distributed decision centres and heterarchical consideration confers a partial autonomy to sub-level decision centres. Second, corrective actions against unexpected events are introduced to maintain as far as possible the forecasted scheduling.

A Process Oriented Manufacturing System Simulation to Measure the Effect of Shop Control Factors

The objective of this paper is to develop a framework for comparing job shop control policies through simulation analysis. A process based simulation model is developed that uses an object oriented data structure. This paper argues that inventory in a job shop should be divided into three categories, and each category's value would be a more useful performance measure for comparing alternate control policies. An experimental design is presented for determining the appropriate shop control rules that combines the major aspects of shop control decisions. The simulation model is flexible and allows specification of an y number of work stations and job types. The model can accommodate both static and dynamic job processing schemes. The model also outlines statistical procedures to compare alternative shop control policies and provides a hierarchical procedure for selecting these rules. The model's applicability is illustrated by testing some shop control rules in a benchmark job shop.

A knowledge based system for combined just-in-time and material requirements planning

A knowledge based simulation model for combined Just-in-Time/Material Requirements Planning systems is presented. The model written in PROLOG includes two expert systems, one for Kanban logic and the other for job shop control. The model is applied to an electronics assembly plant. Factors related to demand variability, vendor lead time variability and buffer sizing are examined. Knowledge based simulation modeling is found to be an effective approach for examining such combined systems in a real world environment.

Integration of job shop control systems: A state-of-the-art review

Integration of job shop control systems: A state-of-the-art review

New logistics and software for job shop control

New software solutions were developed in a novel (fourth) planning stratum for manufacturing within the framework of internal process optimization, allowing almost-real-time lead-time planning as a short-time production process control (foreman's workstation). This solution is connected with a new generation of the external process optimization and thus requires a “variant technology”. Hence, the external process optimization is logically connected with the design steps of “process variant generation”, “process variant optimization” and “multiple-criterion assessment of process variants”; and with the stages of the internal process optimization, namely almost-real-time optimization of lead time and balancing optimization and real-time process monitoring and feedback control.

An artificial intelligence approach to loading workstation resources in a distributed job shop controller

Job shop control involves directing the flow of work through a manufacturing job shop. After reviewing the shop control problem and various approaches towards its solution which have been described in the literature, this paper presents a brief overview of a shop activity manager (SAM), a shop controller which has a distributed architecture and which is based on artificial intelligence (AI) techniques. Attention is then focused on one aspect of the system: the approach used to avoid, as far as possible, overloading any manufacturing resource in the shop with more work than it can handle.

Optimal order-selection policies for a job shop production system

Under Poisson order-arrival, this paper discusses the economics of job-shop production by a policy approach, and presents an operational basis for job shop control. The model consists of job orders with marginal profits, selection function with backlog, and a production centre with fixed capacity. For the two main policies, PSP and DSP, this model is formulated by semi-Markov decision processes, and the operation rate, mean shop-time and reward rate (including idle cost) are obtained. Finally, the relationship of ‘six order-selection policies is given, and the structure of optimal policies is suggested.

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

Abstract 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.

Integration of job shop control systems: A state-of-the-art review

Abstract This paper reviews important theoretical and practical developments in job shop control. The distinguishing feature of this paper is the identification and summary of important concepts and procedures useful for incorporation into computerized job shop control systems. The first section briefly examines the job shop control problem, and presents a broad outline of commonly used subproblems and methods. A review of the past work done in the areas of scheduling and sequencing, workload balancing, work flow structure analysis, and job shop capability evaluation is then presented. The final section lists important concepts and procedures for developing computer integrated job shop control systems.

The Effect of Workload Dependent Due-Dates on Job Shop Performance

This study explores the due-date performance of job shop control systems which base job due dates on a time-phased representation of the workload and the machine capacity in the shop. The performance is measured by the mean and the standard deviation of the lateness. Two parameters are used to vary the functioning of the due-date assignment system: a minimum allowance for waiting, denoted by SL, and a maximum fraction of the available capacity allowed for loading, denoted by CLL. The system increases the waiting lime allowance if congestion is observed when loading a new job. The capability of the system to observe congestion is determined by the parameters CLL and SL. Simulation experiments are used to investigate the performance of the assignment system. It is shown that the assignment system performs quite well with respect to reducing the standard deviation of the lateness; the performance is not very sensitive however to the parameter values used; with an expected capacity utilization of 90%, CLL should be set between 0.80 and 1.00 times the mean available capacity and SL should be set between 0.55 and 0.90 times the mean operation waiting time in the shop. The assignment system may also perform well with respect to controlling the mean lateness. If SL is set between 0.55 and 0.75 times the mean expected waiting time in the shop, a constant mean lateness is obtained independent of the utilization of the shop if CLL is set between 0.70 and 0.80 times of the mean available capacity. However, the mean lateness turns out to be quite sensitive to variations in the job-mix of the workload. Finally it is shown that if the values of the assignment parameters are adequate, the mean job lateness is independent of the number of operations in a job. This property can be used to monitor the correctness of the parameter values.

Scheduling in a batch or job shop production environment

The paper defines batch or job shop production and reviews the functions of production planning and production control in a job shop manufacturing situation. It argues that the separation of planning and control has resulted in the artificial isolation of the sequencing problem in job shop research. It attempts to redefine the production control function for a job shop, now called job shop control, and discusses the activities it involves. The major decision making problems associated with job shop control are highlighted and an objective function of costs to aid in management decision making is evolved. Finally various techniques used to analyse the job shop control problem are briefly reviewed. Digital simulation, it is concluded, offers the best potential because it allows representation of the dynamic behaviour of the job shop in such a way that various policies can be tried out under reasonably realistic conditions and without the major simplifying assumptions necessary if other formulations are to prove feasible.

Job shop control

Abstract The paper defines batch or job shop production and reviews the functions of production planning and production control in a job shop manufacturing situation. It argues that the separation of planning and control has resulted in the artificial isolation of the sequencing problem in job shop research. It attempts to redefine the production control function for a job shop, now called job shop control, and discuss the activities it involves. The major decision-making problems associated with job shop control are highlighted and an objective function of costs to aid in management decision making is evolved.

Note—A Comparison of Capacity Planning Techniques in a Job Shop Control System

A quantitative comparison between three types of capacity planning or shop loading techniques is presented. The results were obtained from simulation experiments.

A Loading and Balancing Methodology for Job Shop Control

An algorithmic procedure is devised for loading and releasing work to a job shop environment. The objective of the procedure is the control and balance of workloads in the shop. The importance of s...

Load Forecasting, Priority Sequencing, and Simulation in a Job Shop Control System

This paper reports the development, installation and evaluation of a simulation which sequences shop operations for the next shift. Simulation outputs give each foreman the priority of jobs currently in his section and those jobs which might be coming through his area during the next work period. The foreman can determine in advance what tools, raw materials, etc., are needed and obtain them, thus tending to eliminate queue time for hot jobs. In three months of operation, the simulation has been more successful than initially expected. Coordination and expediting efforts have been reduced, in-process inventory has been reduced along with worker idle time, and schedule performance has improved. An additional important result noted during this time is an enlargement of the foreman's job. He has less need for coordinators and expediters since he has the information needed to make rational decisions on sequencing the work. This effort illustrates the practicality and desirability of incorporating advanced concepts into operating systems if the system's demands on working personnel are made compatible with the objectives and capabilities of the workers.