Resequencing and feature assignment on an automated assembly line

Abstract

We consider the problem of resequencing a pre-arranged set of jobs on a moving assembly line with the objective of minimizing changeover costs. A changeover cost is incurred whenever two consecutive jobs do not share the same feature. Features are assigned from a set of job-specific feasible features. Re-sequencing is limited by the availability of offline buffers. The problem is motivated by a vehicle resequencing and painting problem at a major U.S. automotive manufacturer. We develop a model for solving the joint resequencing and feature assignment problem and an efficient solution procedure for simultaneously determining optimal feature assignments and vehicle sequences. We show that our solution approach is amenable to implementation in environments where a solution must be obtained within tight time constraints. We also show that the effect of offline buffers is of the diminishing kind with most of the benefits achieved with very few buffers. This means that limited resequencing flexibility is generally sufficient.Furthermore, we show that the value of resequencing is sensitive to the feature density matrix, with resequencing having a significant impact on cost only when density is in the mid range.

Process flexibility: design, evaluation, and applications

“…Lahmar et al (2003) considered the following sequencing problem in an automotive assembly line: cars leaving the body shop on a moving line has to be resequenced prior to entering the paint shop, in order to minimize the changeover cost at the paint shop. Given an initial ordering of jobs, they proposed a Dynamic Program to find the minimum cost permutation of the sequence, so that each position is shifted not more than K 1 positions to the right, and not more than K 2 positions to the left.…”

Sequencing with limited flexibility

“…For example, vehicles leaving the body shop are usually resequenced prior to entering the paint shop in order to minimize the number of paint color changeovers. The resequencing is typically carried out by temporarily pulling vehicles off the line and reinserting them later to form a new sequence (Lahmar et al, 2003). The number of vehicles that can be simultaneously pulled off is limited by the number of available offline buffers.…”

“…One of these problems corresponds to the one addressed by Psaraftis when n i = 1. Lahmar et al (2003) describe a resequencing problem motivated by the automotive industry with a single positionshifting constraint parameter, K, where K is the maximum number of positions a job can shift forward relative to its original position. They also solve for the resequencing problem via a decomposition heuristic.…”

The Car Resequencing Problem with Pull-Off Tables

“…With the help of AS/RS, manufacturers are able to change the order of models between these departments, allowing them to plan and reshuffle optimal sequences according to each department's individual objectives and reconstruct desired model sequences after disturbances during production. Common and widespread forms of resequencing buffers in the automobile industry are selectivity banks (Spieckermann, Gutenschwager, and Voß 2004) and pull-off tables (Lahmar, Ergan, and Benjaafar 2003). Selectivity banks consist of a set of parallel first-in-first-out lanes.…”

“…The use of pull-off tables is only considered in specific mixed-model assembly line settings neglecting the existence of sequencing rules. For example, a variety of papers address sequence alterations in front of the paint shop to build larger lots of identical color (e.g., by Lahmar, Ergan, and Benjaafar 2003;Epping, Hochstättler, and Oertel 2004;Spieckermann, Gutenschwager, and Voß 2004;Lahmar and Benjaafar 2007;Lim and Xu 2009) or in front of final assembly to level the material demand (Boysen, Fliedner, and Scholl 2010). Other resequencing papers either deal with buffer dimensioning (Inman 2003;Ding and Sun 2004), alternative forms of buffer organization, e.g., mix banks (Choi and Shin 1997;Spieckermann, Gutenschwager, and This paper introduces the car resequencing problem (CRSP) which assumes a given model sequence and returns a strategy how to use pull-off tables to minimize violations of sequencing rules in the resulting sequence.…”