Showing papers on "Job shop published in 1986"

A Tactical Planning Model for a Job Shop

Abstract: We propose and develop a discrete-time, continuous-flow model for studying the operation of a job shop that sees a stationary input mix of job types. We are not concerned with issues of detailed scheduling, but rather hope to develop a tactical planning tool for a job-shop operation. With the model, we are able to characterize the operational behavior of each work center in the job shop for a given control policy. The control rule sets the production rate at a work center as a fixed proportion of its queue level in each time period, and is consistent with the assignment of a planned lead time to each work center. For these control rules, the model gives the steady-state distribution of the production levels at each work center, as well as the distribution of queue lengths. We show how to use the model not only to evaluate a choice of the controls but also to find a good specification that results in acceptable shop behavior. An example for a factory that produces grinding machines illustrates the use of the model.

A simulation comparison of group technology with traditional job shop manufacturing

Abstract: A simulation model of an actual job shop was used to compare group technology with traditional job shop manufacturing. The experiment compared shops which had four different layouts, designed to emphasize different features of traditional job shops and group technology shops, and four distributions of demand for end items. The group technology shops exhibited superior performance in terms of average move time and average set-up time. The traditional job shops had superior performance in queue related variables (average queue length, average waiting time, work-in-process inventory, etc.). This was caused by group technology's dedication of machines. The effects of the queue related variables outweighed the effects of average move time and average set-up time: the average flow time was shorter in the traditional job shop than in the group technology shops.

A Heuristic for Multiple Lot Sizing For an Order Under Variable Yield

Abstract: Consider a job shop which must completely fill a large make-to-order demand of a product where production yield is highly variable. After a production lot is completed, if the total output of satisfactory units is inadequate to satisfy the demand, then a new run (with associated setup cost) is made. When the output of good units exceeds the demand, then the excess units are scrapped (with possible salvage value). The optimal lot size minimizes the total of production, setup, holding, shortage, and scrap costs. A heuristic is developed based on the incremental cost of increasing the lot size by one unit. The computational ease and excellent cost performance of the heuristic favor its use in place of the mathematically optimal solution obtained by dynamic programming. Real world manufacturing applications and additional properties of the model are also discussed.

Decision-aid in job shop scheduling: A knowledge based approach

Abstract: This paper deals with operation scheduling on machines in a job shop. The jobs which consist of a set of related operations are supposed to be constrained by limit times (earliest starting times and due dates). The approach aims at generating restrictions on local scheduling decisions by only considering limit times and resource availability constraints (constraint based analysis). This is achieved through an inference process which is defined from generic knowledge arising in scheduling problems : limit times associated with each operation, logical sequencing conditions between operations, inference rules relating to limit times and sequencing conditions. A software implementation in PROLOG of a constraint-based analysis module is presented. Such a module may be used either in a static way in order to generate a plan over a certain horizon or in a dynamic way in order to help in making real time decisions. In this last case it can be held to act the part of a flexible planning function.

Optimal due-date assignment in a job shop†

Abstract: SUMMARY This paper presents an analytical model for determining the optimal processing-time and number of operations multiples for the TWK and TWK + NOP due-date assignment methods in a dynamic job shop subject to restrictive assumptions on queue discipline and processing time distribution. The analytical results are compared with the experimental results obtained from simulation of a hypothetical job shop under various shop conditions. The close agreement of the results reveals the validity of the analytical model. In addition, the results show that the TWK + NOP method is more effective in minimizing the missed due-date cost in a job shop.

A SLAM II simulation study of a simplified flow shop

Abstract: Control of jobs being processed in a flow shop is important to management. Shop performance is affected by shop congestion, processing time variation, and the dispatching rule used to load the jobs. Most previous research has concentrated on the effects of varying these parameters in a job shop setting. A SLAM II net work model and simulation analysis of these parameter varia tions was applied in a two-work center flow shop. Performance of the flow shop was tested using combinations of 5 dispatching rules, 3 shop load levels, and 2 levels of processing time varia tion. Based on a series of performance measures, the shop using the shortest processing time dispatching rule in one work center and the due data based rule in the other compares favorably with the shop that used the shortest processing time rule in both work centers. Results indicate that shop congestion and process ing time variation affect the performance of the flow shop as well. Performances between the flow shop and job shop are com pared, ...

Inequalities for stochastic flow shops and job shops

Abstract: Consider an m-machine flow shop with n jobs. The processing time of job j, j = 1,…, n, on each one of the m machines is equal to the random variable Xj and is distributed according to Fj. We show that, under certain conditions, more homogeneous distributions F1,…, Fn result in a smaller expected makespan. We also study the effect of the variability of distribution Fj on the expected waiting costs of the n jobs and on the job sequencing which minimizes this total expected waiting cost. We show that the smallest (largest) variance first rule minimizes the total expected waiting cost on a single machine when the waiting cost function is increasing convex (concave). We also show that the smallest variance first rule minimizes, under given conditions, the total expected waiting cost in an m machine flow shop when the waiting cost function is increasing convex. Similar results are also obtained for the two-machine job shop. Similar results cannot be obtained when the processing times of job j on the various machines are i.i.d. and distributed according to Fj.

Effects of fluctuations in the quantity of work arriving on waiting time, idle time and rate of losing customers

Abstract: SUMMARY In a job shop, the intervals between job arrivals and the job processing times fluctuate and cannot be forecast. When many jobs (customers) arrive at a job shop at the same time, some customers may not place an order because they do not want to wait. To prevent such a situation, the job shop may temporarily increase the process capacity, thereby reducing the waiting time. If its timing is not correct, however, such an increase can also unexpectedly increase the idle time in the process. In this paper, the effects of fluctuations in the quantity of work arriving on waiting time, idle time and the rate of losing customers is studied using numerical calculations which assume extreme fluctuations. These characteristics show different delays in their response to fluctuations in job arrivals. The paper deals with the index and timing for temporarily increasing and decreasing the process capacity to absorb the fluctuations in the quantity of work arriving, that is under what circumstances to do so and when.

General theories of flexible integration

Abstract: The three basic categories of manufacturing are the job shop, the transfer line and the flexible manufacturing system (FMS) Each can be considered the result of evolving manufacturing requirements The FMS, first introduced in the early 1970s, is the most recent solution to manufacturing problems and it is constantly being improved as the technology evolves The FMS allows production volume to be increased or decreased and allows the product to be varied within specific limits

Decision aids for the management of large non-job shop type manufacturing systems

Abstract: In this paper we examine the problems of management and control of large scale multi-product multi-line batch manufacturing outside the mechanical engineering industries. The main examples of such non-job shop type manufacturing arises in the making of frequently purchased products e.g. small consumer goods, processed foods, cigarettes, candy, etc. The decision making problems which arise in such systems are extremely complex and the decision support tools for helping management at various levels could be of significant advantage in improving the productivity of such businesses. This paper describes a number of decision support tools which could be used at the different levels of the production hierarchy. The production hierarchy in virtually all manufacturing can be conveniently divided into 4 levels each of which is characterised by a significantly different time scale from that of the other levels. At the highest level, the time horizon of interest is 1 to 5 years and the decision making is of a strategic nature. At the next level down where the time horizon of interest is from 1–2 months to 1 year, the decision making is operational/tactical. The third level down concentrates on issues of production planning and scheduling and its horizon of interest varies from 1 hour to about 20 weeks. The lowest level deals with disturbances occurring over a very short horizon (a few seconds to about 1 hour) and at this level, most of the decision making is automatic (PID controllers, optimal control, self tuning regulators, etc.). Each higher level provides performance targets for the next level down. In this paper we examine the main issues which arise at the top three levels in the hierarchy and describe some decision support tools which have been developed by the author and others. At the top two levels the tools are designed to cope with the issues of competition whilst at the lower level (production planning and scheduling) the problems of allocating tasks to limited resources in the most cost effective way are addressed. Overall, we show how improved efficiency at each level can lead to significant improvements in productivity.

Qualification based production — the superior choice to the “unmanned factory”

Abstract: Governed by political-economic factors rather than technical necessities, the past development of small batch production has led to advanced horizontal and vertical division of labor, job shop manufacturing, and the use of NC machines. This caused serious difficulties such as long and variant throughput times, an unfavourable ratio of unproductive to productive workers, and low quality of work. Additionally confronted with deeply changed market conditions, the management is split in tow lines struggling for the right answer to this challenge. Most managers and production planners try to replace human work still further by enforced use of computers on the shop floor and in the technical office in an integrated manner (CIM). Since this strategy is in danger to create new severe problems, the minority seeks to avoid them by reorganizing production and rearranging the division of functions between man and machine profoundly (skill based production). This position is outlined in some detail including examples of realized subsystems as first steps on this development path. Finally, reasons for superiority and forces of inertia are discussed.