Suchergebnisse

ABSTRACTThis study investigates the impact of planned lead times on performance in multistage manufacturing where material requirements planning is used in a make‐to‐stock environment. We simulate a variety of different operating environments and find: (1) planned lead times are important to customer service levels under all operating environments examined, but have a smaller impact on inventory investment; (2) tight due dates introduced by short planned lead times hurt customer service without saving much inventory; (3) small increases to tight planned lead times improve customer service substantially with small inventory increases; (4) co‐component inventories change with planned lead times, and disparity between such inventories is a sign of poor timing coordination; (5) the fixed order quantity rule performs better than the periodic order quantity rule; and (6) tall product structure and large lot sizes require particular attention to planned lead times. The findings also extend the current understanding of planned lead times by including uncertainties such as forecast error, yield loss, and equipment reliability. The study concludes with a way to diagnose and improve poorly set planned lead times.

ABSTRACTWe test the situational impact of two types of resource flexibility, machine flexibility and labor flexibility, in a material requirements planning (MRP)‐driven production system. Machine flexibility has not been treated in prior multistage research, only labor flexibility. Machine flexibility is closely related to a plant's positioning strategy. A process‐focused plant opts for considerable machine flexibility by choosing general‐purpose equipment. Resource flexibility, if effective, can be an attractive alternative to two other types of buffers, inflated inventories and costly capacity cushions.Our simulation results, using factor settings established earlier by a panel of managers, show that resource flexibility is indeed an effective buffer against uncertainties such as end‐item demand variability, capacity bottlenecks, equipment failures, and yield losses. Machine flexibility is especially helpful in environments characterized by high uncertainties, tight capacities, and large lot sizes. Worker flexibility has a similar, but less dramatic, impact. Benefits are most striking with customer service, rather than with inventory or labor productivity. Finally, we show that simultaneous introduction of both machine and labor flexibility yields only marginal improvements over either kind of flexibility alone.

ABSTRACTThe purpose of this research is to determine if prior findings that favor simple forecasting techniques and technique combinations hold true in a short‐term forecasting environment, where demand data can be quite volatile. Twenty‐two time series of daily data from a real business setting are used to test one‐period ahead forecasts, the epitome of short‐term forecasting. The time series vary systematically as to data volatility and forecast difficulty. Forecast accuracy is measured in terms of both mean absolute percentage error (MAPE) and mean percentage error (MPE).

ABSTRACTThis paper describes a methodology to treat multiple objectives in a mathematical programming problem. A linear programming model is developed for the short‐term manpower scheduling problem in a post office so as to get a desirable balance between mail transit times and resource expenditures. The scheduling problem is of particular interest because of 1) the multiplicity of objectives, 2) the existence of several mail classes, each having different arrival patterns, routings, and dispatch times, and 3) the complexity of the different scheduling options available. The paper demonstrates how the model can be used experimentally to obtain model parameters which, in the judgment of management, achieve a desirable balance between objectives. Once the parameters are determined, the model prescribes how to vary the overtime usage, reassign workers to the various work stations, and adjust the priorities of the mail classes. The model has indirect use in studying the effects of changing work capacities, dispatch schedules, and mail arrival patterns.

ABSTRACTThis paper addresses a class of problems, referred to as "disaggregation problems," which lie between planning at the top level and the more detailed decisions of inventory control and scheduling at the bottom level. Most real‐world problems are sufficiently complex to warrant a sequential or top‐down approach to problem solving. However, researchers have paid scant attention to disaggregation until very recently. The resulting lack of an interfacing mechanism diminishes the utility of solution procedures for aggregate planning, inventory control, and scheduling. In order to draw attention to this gap, a taxonomy of disaggregation problems is developed for both manufacturing and service organizations. The purpose is to identify and classify problems, describe representative research, and identify unresolved issues.

ABSTRACTIdentifying manufacturers' competitive priorities has long been considered a key element in manufacturing strategy research. However, relatively little effort has been devoted to measurement of these constructs in published research. In this study we develop scales for commonly accepted competitive priorities, cost importance, quality importance, delivery‐time importance, and flexibility importance. We assess how well the scales capture the constructs that they represent using data collected from 114 manufacturing plants in the United States. The findings suggest that the instrument developed can provide reliable data and that the constructs measured are valid. In addition, comparisons between pairs of informants representing the same business indicate that the perceptual measures of competitive priorities are as reliable as point estimates of routine, seemingly objective information.

ABSTRACTDeveloping a better understanding of the impact of uncertainty on process performance has been recognized as an important research opportunity in service design (Hill, et al., 2002). Within this general research stream, our study focuses on the question of what managers can do to most effectively address operational uncertainty and mitigate its negative effects. To begin to address this question, we report on an exploratory study using a sample of professionals in the financial‐services industry who acted as informants on 108 financial‐services processes. These professionals were sampled from a population of graduates of a university in the northeastern region of the United States who were employed in the financial‐services industry. Based on these processes, we empirically examine the relationship between responses to operational uncertainty and process performance after controlling for customer mix, other uncertainty sources, and process type characteristics. Our findings suggest that process improvement—an uncertainty reduction approach related to the internal functioning of the process—as well as several uncertainty coping approaches are associated with better performing processes. However, uncertainty reduction approaches related to customer involvement with, and demands on, the process are not associated with better performing processes. We discuss the implications of our findings for determining what actions managers can take to reduce the negative performance effects of operational uncertainty and how managers can decide which of these actions to take. We conclude with a discussion of the limitations of our study.

ABSTRACTManufacturing strategy reflects the goals of the business strategy and directs the manufacturing function in achieving them. In this study, we focus on two decision areas with crucial implications for manufacturing strategy: product planning and process design. Using mathematical programming models as a research tool, we test several conjectures in the manufacturing strategy literature regarding linkages between the two decisions.Our results show that a close integration between these decisions helps control the product offerings, stabilize process requirements, improve process technology choices, and increase net cash flows over time. Using the concept of environmental clusters, we found that a close linkage is more critical when the environment is more complex, less uncertain, and tighter. Based on these findings, we present some managerial implications and suggestions for future research.

1. Perspectives on disaggregation -- 2. Disaggregation in manufacturing and service organizations: survey of problems and research -- 3. Toward a theory of hierarchical coordination and conflict -- 4. An MSA view of disaggregation -- 5. Hierarchical planning systems: a production application -- 6. Optimal aggregation and disaggregation in hierarchical planning -- 7. A hierarchical approach for the planning of a complex production system -- 8. A hierarchical approach to multilocation inventory systems -- 9. A disaggregation problem and a search enumeration algorithm for a multiplant, multiproduct scheduling application -- 10. An efficient algorithm for multi-item scheduling -- 11. Large scale optimization for master production scheduling -- 12. Multi-item scheduling with reflection programming -- 13. An approach to the analysis of integrated production-distribution systems -- 14. Empirical relationships among budgets, other financially-oriented aggregate plans, and the master production schedule (MPS) -- 15. Hedging the master schedule -- 16. The disaggregation problem in the paper industry -- 17. An economic lot size algorithm for multi-level inventory systems with acyclic network structures -- 18. Impact of a product structure measure on the effectiveness of lot sizing techniques -- 19. The effects of joint lot size strategies on capacity related performance in a multi-stage production-inventory system -- 20. The impact of capacity on lot sizing decisions -- 21. Variations in optimizing serial multi-stage production/inventory systems -- 22. Priority updating procedures in dynamic job shop simulation studies: the impact on measures of performance under different due date assignment rules -- 23. A review of flowshop scheduling research -- 24. An aggregate-disaggregate approach to the large scale multiple project scheduling problem -- 25. Shift scheduling for telephone operators and service office employees -- 26. A complete control system for workforce management at a post office -- 27. Decision making in the public sector: an application of goal interval programming for disaggregation in the post office -- 28. Disaggregation of manpower in a service organization -- 29. Facilities planning in the railroad industry: the need for disaggregation -- 30. Vehicle dispatching — sweep algorithm and extensions -- 31. Navy enlisted manpower planning -- 32. A public policy optimization model with simulation of disaggregation aspects: formulation of energy R and D policy -- 33. Costs and benefits of a computer based regional blood inventory system -- 34. Multi-level police patrol planning -- 35. Disaggregation of the decisions to allocate patrol resources to police precincts -- 36. Economically optimal quantity and mix of fire department services -- 37. Disaggregation planning, scheduling and allocation of nursing staff -- 38. 'Disaggregate mathematical models of optimal hospital bed management -- 39. Recursive modeling of outpatient health care settings -- 40. Nurse scheduling: a case of disaggregation in the public sector -- 41. Computerized scheduling of hospital nursing personnel: disaggregation to accommodate individual preferences and nonroutine constraints -- 42. Disaggregating health utilization data for planning -- 43. Scheduling workers in situations having highly variable manpower requirements -- 44. Optimal scheduling of two consecutive work periods -- 45. A simple method for obtaining cyclic employee schedules -- 46. Heuristic work force scheduling with variable shift lengths and labor productivity differences: a case study of encoder staffing.