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An existing taxonomy of workload control rules is adapted to classify 25 workload control rules and their components examined in prior research to create a basis to model how three workload control rule components – order selection, work aggregation and buffer limits – affect shop performance in environments that differ in their bottleneck utilization and protective capacity levels. Two of the most frequently studied rules in the literature – CONWIP and DBR – were included in the simulation. Data analysis found that the workload control rules had a significant positive effect on the shop performance measures only in environments with the highest bottleneck utilization and the lowest protective capacity. However, the work aggregation method was found to be an important component of the workload control rule. Suggestions were made for future research that could increase our understanding of workload control rules and integrate this research with our understanding of lean production.

Emerging research strengthens the connection between supply chain performance and a company's financial performance (D’Avanzo, R., Von Lewinski, H. and Van Wassenhove, L. N., 2003. The link between supply chain and financial performance. Supply Chain Management Review, November/December, 40–47). The focus on integrating functional internal processes has expanded to include the need for integrating these with external processes of business partners (Edwards, P., Peters, M. and Sharman, G., 2001. The effectiveness of information systems in supporting the extended supply chain. Journal of Business Logistics, 22(1), 1–27). This need for enterprise efficiency is compelling companies to review, to identify, and to adopt supply chain initiatives. This research investigates the use of common measurement metrics in an attempt to determine which one(s) are most useful for measuring performance as companies implement SCM practices. For firms that were engaged in SCM we found inventory and cycle time to be the most s...

As competition has intensified for both domestic and international firms, so has the need to increase operating and production efficiency and reduce costs, implying an increasing focus on integrating processes and sharing data between business partners (Edwards, Peters, & Sharman, 2001). The purpose of this study is to examine the state of data sharing practices between companies within a supply chain configuration and to assess the pervasiveness with which data moves beyond company boundaries.Our findings indicate that the number of tiers data shared correlates significantly with firm performance, but that the type of data shared varies depending on whether the partner is a customer or supplier. Customers appear more likely to receive inventory data and suppliers are most often provided forecast data. The sharing of data is most profound with adjacent supply chain partners. However, it is not uncommon for data to be shared directly with a nonadjacent supply chain member. The number of tiers moderated the...

Processing times are difficult to accurately estimate in industries where custom-designed products are dominant. When schedulers are unable to make accurate estimates, what is the effect of estimation errors on the performance of scheduling policies? Processing time uncertainty (PTU) has become a focus of researchers in the production scheduling area. However, previous operational definition of PTU confounds the estimation error with the variation of actual processing time. In order to determine the effect of estimation errors, a thorough reexamination of prior studies becomes necessary. The results from our simulation experiments show that the estimation error has only a trivial effect on the performance of scheduling policies, and imply that the variation of actual processing time has a more important effect than the estimation error of processing time. The results from our simulation experiment have been verified by probabilistic analysis and Little's law.

Spare parts inventories are not intermediate or final products to be sold to a customer, and the policies that govern spare parts inventories are different from those which govern WIP and other inventories. This paper is an update of the discussion of maintenance inventories and a discussion of the future research needed. After a discussion of unique aspects of spare parts inventories, literature is reviewed which relates to management issues, age-based replacement, multi-echelon problems, problems involving obsolescence, repairable spare parts, and special applications.

Protective capacity is the 'extra' capacity placed at non-bottleneck resources to absorb random disruptions in planned levels of performance so that the bottleneck resource continues to be effectively utilized. A full factorial experiment with a simulation model was conducted to explore issues associated with the quantity and location of processing variance in a five-station manufacturing cell. The cell's performance was measured using both mean flow time ( MFT ) and bottleneck shiftiness ( SHIFT ) for 3 patterns of variance for the non-bottlenecks at 5 different levels of variation. In order to investigate the importance of the quantity of added capacity on the variation both a low level of protective capacity (10%) and a high level (50%) were considered. The results indicate that having the higher variation work centres close to the bottleneck provides reduced MFT and SHIFT . The performance measures improved at both the low and high setting of protective capacity.

The primary objective of this work was to evaluate how four important system parameters (schedule frozen interval, schedule re-planning interval, safety stock and lot-sizing rules) affect material requirements planning (MRP) system performance in terms of schedule instability, total cost and service level, considering different levels of two operating factors: the lead-times of items in the product structure, and the accuracy of the demand forecast. The research design employed a simulation model in Visual Basic run on a personal computer. This study concluded that all system parameters and operating factors significantly influence the three performance measures. Frozen interval, forecast accuracy, and lead-time have the most significant impact on system instability and total cost. Forecast accuracy, safety stock, and lead-time have the most impact on service level. Due to the interactions among system parameters and operating factors, there are no win-win principles to set parameters in order to achieve ...

Protective capacity is the `extra' capacity placed at non-bottleneck resources to absorb random disruptions in planned levels of performance so that the bottleneck resource is more effectively utilized. Although informative, the research related to protective capacity offers little insight into the preferred placement of protective capacity. By building on the existing research, our study develops hypotheses related to protective capacity positioning and then tested them by using a simulation model of a manufacturing cell. The results indicate that the placement of the protective capacity has no practical influence on mean flow time, but it strongly influences bottleneck shiftiness. Specifically, the study's results may indicate that under conditions of high work center utilization, the placement of protective capacity immediately before and after the bottleneck with a higher proportion distributed to the upstream work centers may significantly lower bottleneck shiftiness. Several future research needs are discussed.

A recent paper discusses a capacity rationing policy that allows make-to-order manufacturing firms encountering expected total demand in excess of available capacity to discriminate between two classes of products, one yielding a higher profit contribution per unit of capacity allocated to it than the other. The result is a selective rejection of orders for the class with lower unit contribution, yielding an increase in total profit when compared to a base case that implements no capacity rationing. Implementation of the policy requires forecasts of demand parameters for both product classes. In this paper we test the sensitivity of the capacity rationing policy to forecast errors in these parameters. The results indicate that, on average, the rationing policy is quite robust in improving profit even when actual demands are approximately twenty percent different from forecast values.