We address the problem of sequencing jobs, each of which is characterized by one of a large number of possible combinations of customer-specified options, on a paced assembly line. These problems arise frequently in the automotive industry. One job must be launched into the system at equal time intervals, where the time interval (or cycle time) is prespecified. The problem is to sequence the jobs to maximize the total amount of work completed, or equivalently, to minimize the total amount of incomplete work (or work overload). Since there is a large number of option combinations, each job is almost unique. This fact precludes the use of existing mixed model assembly line sequencing techniques. We first consider the sequencing problem for a single station which can perform two different sets of operations. We characterize the optimal solution for this problem and use the results as the basis for a heuristic procedure for multiple stations. Computational results with data from a major automobile company are reported.assembly lines, sequencing, dynamic programming, heuristics

PurposeThe purpose of this paper is to present empirical results of an analysis of the strategic alignment between order winners selection and external supply chain integration strategies.Design/methodology/approachThe research instrument is an international survey from IMSS II. It was applied in 23 countries. ANOVA was used for statistical analyses.FindingsThe findings show that firms choosing to use price as an order winner do not show any significant difference in the extent of external supply chain integration. On the other hand, firms that use delivery, customer service, quality and/or flexibility as order winners present differences in the extent to which they integrate their external supply chains.Research limitations/implicationsThe results should be treated with caution as any empirical study due to generalizability concerns. The data do not necessarily imply causal relationships, which could be an interesting topic to explore in further research.Practical implicationsThe study highlights the importance of supply chain integration as a competitive competence, meriting management consideration and resources.Originality/valueThe paper shows empirical evidence with a large sample size that some associations exist between external supply chain integration and order winning strategies.

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Dynamic scheduling of manufacturing systems for due date based objectives has received considerable attention from practitioners and researchers due to the importance of meeting due dates in most industries. Research investigations have focused primarily on the relative effectiveness of various dispatching rules in job shops. These rules operate by prioritizing jobs using a “criticality index” based on job and system status. Jobs are then scheduled from most critical to least, with the indexes typically being updated as the system changes. This study considers two important issues which have not been addressed previously in the literature. First, we investigate the impact of unequal machine workloads on the relative effectiveness of dispatching rules. This is significant because workloads are likely to be unbalanced in most real systems. While it is clear, intuitively, that this imbalance in machine workloads is likely to deteriorate system performance, it is not obvious whether the superiority of certain dispatching rules established in earlier studies for balanced workloads is carried forward to this case. We show that the performance of different dispatching rules does indeed depend upon the degree of workload imbalance. We also propose and test a scheduling procedure which performs well in both balanced and unbalanced systems. Next, we develop a scheduling approach which shows promise as being an improved alternative to the use of dispatching rules. This approach decomposes the dynamic scheduling problem into a series of static problems. These static problems are then solved using an optimum‐seeking method, and the solutions are implemented on a rolling basis. We show through a simulation experiment that adopting this approach over dispatching rules leads to an improvement in the overall solution quality, even in a dynamic environment. The two very practical implications of our study are: (1) that commonly used dispatching rules in job shops or automated manufacturing systems may not be the best approach when capacity utilization is unbalanced (2) a job shop or automated manufacturing system would likely benefit from implementing optimal‐seeking scheduling rules instead of the traditional job dispatching rules.