ANALYTICAL TOOLS FOR ASSEMBLY LINE DESIGN AND SEQUENCING

Many complex assembly lines, such as those in the automobile industry, have dozens or hundreds of stations that are affected by customer-selected options on the jobs being assembled. The various options often require significantly different amounts of processing time, and the role of assembly line sequencing in this context is to smooth out the flow of work to each station. However, most assembly line sequencing algorithms developed for such situations cannot consider so many stations or options effectively. In this paper, we develop an analytical method to compute a criticality index for each station, which can be used to determine which stations are most important to include in an assembly line sequencing algorithm. We report computational results using actual industry data which indicates that substantial improvements can be obtained by selecting stations based upon this criticality index.     

A COMPUTER METHOD OF SEQUENCING OPERATIONS FOR ASSEMBLY LINES

COMSOAL, an acronym for a computer Method of Sequencing Operations for Assembly Lines, is a method of balancing large complex machine-paced assembly lines. Basically, by means of a high-speed digital computer, sampled data is used for Monte-Carlo simulation of the proposed designs.

COMSOAL originated in an industrial operations research project and is in use at some factories of the Chrysler Corporation in an early form. The latest version, described here, awaits implementation in the factory situation.

First, the problem is analyzed in simple form and two solutions are offered, with several results, arising from applications to situations with up to 1000 tasks. The analysis is then extended and solutions to the complex form, which includes eight typical additional constraints, mixed production and stochastic considerations, are presented     

BATCHING AND SEQUENCING OF COMPONENTS AT A SINGLE FACILITY

We formulate and solve a single-machine scheduling problem where each job requires a component unique to that job and one which is common to all jobs. We develop an optimal dynamic programming algorithm for this problem which minimizes total job flow time. In addition we show that scheduling jobs rather than components efficiently is desirable and may lead to improved coordination between production and assembly.     

A ROLLING HORIZON HEURISTIC FOR REACTIVE SCHEDULING OF BATCH PROCESS OPERATIONS

Batch chemical plants are dynamic processing facilities where static production schedules can rarely be adhered to due to market and operating uncertainties. On-line schedule modification of a prior; timing assignments and resource allocations in response to unantipicated disruptions is done through a decomposition heuristic that uses a rolling horizon implementation policy. An attempt is made to minimize the impact of the disruptions on the original schedule near the point of each deviation while exploiting the combinatorial flexibility of task and resource reassignments in future scheduling time windows. The problem is addressed as a multiobjective optimization problem involving completion time criteria, relative customer importance, and production cost considerations.

A rigorous analysis of problem sensitive parameters, including penalty weights and subhorizon length, is conducted. A model plant case study is performed. Variations on storage availability and task flexibility are investigated in an attempt to characterize dominant effects of the weighting parameters. Results indicate that user preference can serve as a strong guide for obtaining near optimal reactive scheduling solutions. It is shown that the combinatories can be controlled and that costly and inefficient full scale rescheduling of multipurpose production facilities can be avoided.     

BATCH SCHEDULING TO MINIMIZE CYCLE TIME, FLOW TIME, AND PROCESSING COST

We consider a multi-stage batch processing system in which a group of identical units, requiring the same set of operations, is manufactured. In this system, work on the batch must be continuous at each operation, but the batch can be split into sub-batches for transfer between consecutive operations. We examine the case in which operations can be performed in any sequence, using cycle time, total flow time (static and dynamic), and processing cost as measures of performance. It is shown that these problems are closely related to a traveling-salesman problem with a special cost matrix. Optimal scheduling rules are developed for all measures of performance.     

ON THE DUALITY APPROACH TO OPTIMAL DUE DATE DETERMINATION AND SEQUENCING IN A JOB SHOP

This paper considers the problem of finding an optimal CON due date and sequencing of n independent jobs to be processed on a single machine by minimizing the total value of lateness. A linear programming model is developed to find an optimal CON due date which is solved by considering its dual. A procedure to find the optimal job sequence is then presented and elaborated by a numerical example.