bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sequential facility location with distance dependent demand
Authors: Oded Berman , Celik Parkan 
Published: October 2002

AbstractSystems providing identical service to many population centers frequently face the issue of where to locate the next retail outlet, branch, store, etc. In such systems the demand for the facilities' service depends mainly on the distance between facilities and customers. It is assumed that there are already m facilities located on a network to respond to the demand at the nodes. The paper addresses the problems of finding a location on the network for the (m + 1)st facility corresponding to a given total expected demand and of determining which demand points will be served by which facility. Also the range of the total expected demand values that can be realized along each link in the m + 1 facility system is determined. Examples and a discussion of the results are provided.
Capacity planning techniques for manufacturing control systems: Information requirements and operational features
Authors: Berry William L. , Schmitt CPIM Thomas G. , Vollmann Thomas E. 
Published: October 2002

AbstractSubstantial interest has been focused on techniques that determine the amount and timing of work center capacity to satisfy the master production schedule. Although several techniques have been developed for preparing work center capacity plans, very little analysis of the operational features and the application of these techniques has been reported. Four techniques, capacity planning using overall factors (CPOF), capacity bills, resource profiles, and capacity requirements planning (CRP), vary substantially in their complexity and the level of detail required to plan work center capacities. All four procedures require the use of the master production schedule to develop a capacity plan, but some have much more demanding data requirements. Important differences are the means by which capacity requirements are estimated by the techniques and the manner in which the bill of material, manufacturing lead time and inventory status information are incorporated into the capacity plan. The purpose of this paper is to describe the operational features of the four capacity planning techniques, the underlying data base requirements, and some key managerial issues in choosing among these techniques.
PDF versus LP: An empirical aggregate planning comparison
Authors: Holt Jack A. 
Published: October 2002

AbstractProduction Decision Framework (PDF) is a recently introduced heuristic method for solving the aggregate planning problem. The algorithm was developed and tested over a wide range of deterministic demand patterns and cost parameters. The decision by Wayn‐Tex Inc., to adopt the methodology provided a real world opportunity to evaluate the performance of PDF under uncertainty over a one year's operating period.This paper concentrated on a study of (1) the effectiveness of the model in selecting a suitable rolling planning horizon, and (2) the performance of PDF as compared to a linear program solution using the same length horizon. The monthly sales forecast used in the study, developed by the sales department, took into consideration trend, seasonality, and known market conditions. The results were gratifying. Management has indicated their desire to continue using PDF as a guide in the production planning process through the use of the computerized program available.
The effects of input control in a simple scheduling model
Authors: Baker Kenneth R. 
Published: October 2002

AbstractInput control is a generic procedure for smoothing production workload by delaying work during intervals of heavy load. While input control techniques have several practical benefits, they also have an inherent disadvantage. By restricting the set of jobs available for scheduling, an input control procedure removes some of the scheduling options that would otherwise be available. This paper examines the impact of such a procedure in a simple simulation model.The simulation model represents a production shop in a simplified way, as a single machine, but the production control system has three distinct parts. The first part assigns due‐dates to customer orders, taking into consideration the size of each job and the workload in the shop. The second part is a job releasing rule that implements input control. The third part is a priority dispatching procedure that is aimed at meeting due‐dates. By representing this three‐part control system the model provides an opportunity to explore the interdependence between input control and other control procedures.Reinforcing previous research, the simulation experiments confirm that modified due‐date priorities perform more effectively than other basic priority rules when performance is measured by average tardiness. Moreover, the experiments indicate that performance under the modified due‐date regime is never improved by the use of input control. On the other hand, with dispatching rules that rely on shortest‐first or critical ratio priorities, the experiments indicate that input control is sometimes advantageous. The effects of input control on scheduling performance thus appear to be somewhat complicated, and further experiments were designed to explore some of the relationships involved. The principal finding, however, provides a warning that input control can be counterproductive.
Integer goal programming for multistage lot sizing: Experimentation and implementation
Authors: Vickery Shawnee K. , Markland Robert E. 
Published: October 2002

AbstractThis article considers the issues involved in implementing a large‐scale multistage lot sizing model in a pharmaceutical manufacturing environment, and reports on a series of sensitivity experiments that subsequently examined the critical impacts of system capacity and inventory policy on the specification of a multistage schedule. The model was initially developed as an aggregate scheduling aid for a class of tablet pharmaceuticals. The manufacture of tablet products is a serial‐type process characterized by batch flow. The model placed multiple resource capacity restrictions on various stages of the multistage system to ensure the feasibility of the resultant schedules. Difficulties in estimating penalty costs for shortages were circumvented by employing a multi‐objective formulation of the lot‐sizing problem.Various obstacles encountered during the implementation process are discussed. Model implementation encompassed the development of an approximation algorithm for efficiently solving the large‐scale problem. The performance of the algorithm was evaluated by examining the closeness to optimality of the solutions obtained using the procedure. Performance statistics are presented for the sensitivity experiments discussed herein. Another essential aspect of implementation involved the timely revision of model input parameters. This facet of implementation proved to be at least as important to management as the efficient provision of a “good” solution.Model experimentation centered on variations in the capacities of bottleneck resources and changes in target inventory parameters whose values are predetermined by company policy. The first set of experiments was designed to demonstrate the importance of system capacity to the lot‐sizing process and to illustrate that the location of a system bottleneck can vary over time as a function of both internal and external factors. The results indicated that lot‐sizing procedures that fail to incorporate capacity information or that focus on a single bottleneck production stage in order to schedule production are severely limited with respect to practical and/or long‐term applicability.The final set of inventory‐related experiments indicated that the specification of target ending inventory levels was a crucial factor in the lot‐sizing process. The determination of appropriate target levels must reflect the inherent trade‐off between the objective of minimizing shortages and the desire to avoid excessive inventory accumulations. The generation of usable model information was found to be contingent upon the realistic definition of target level parameters.
A reformulation of the aggregate planning problem
Authors: Schroeder Roger G. , Larson Paul D. 
Published: October 2002

AbstractThis article proposes a reformulation of the aggregate planning problem which more closely agrees with situations frequently encountered in practice. The proposed reformulation assumes that a firm's production planners want to determine the expected service and inventory levels for a given production profile in the face of uncertain seasonal demand. By using several different production profiles that are each consistent with the firm's staffing, subcontracting, and overtime policies, it is possible to pick the profile that best meets the firm's preferences for service level and inventory turns. Actually, the trade‐offs between inventory and service levels are examined so that an informed choice can be made by all of those concerned.One of the advantages of the proposed model is that communications can be established among production, marketing, and finance managers who often have conflicting goals. Also, levels for inventory turns, service, and production can be set that are consistent with each other. Furthermore, several alternative production profiles can be examined in a relatively short time through the use of the simulation model proposed.An application of the model to the Wagner Spray Tech Company, a producer of painting equipment, is presented. In this particular case, where forecasting errors are quite high, some of the potential uses of the model are presented. Also, reasons are given why this particular reformulation of the aggregate planning problem was found to be useful.
The effect of lead‐time variability: The case of independent demand
Authors: Bagchi Uttarayan , Hayya Jack C. , Chu Chao‐Hsien 
Published: October 2002

AbstractWe show in this study, through analysis and examples, the impact on stockouts and stockout risk if the variability of lead time in independent demand systems is ignored. In calculating safety stocks, we recommend that the compound distribution of demand during lead time, or a good approximation to it, be used. We motivate the article by a case study on lead‐time variability at the U.S. Air Force and show the impact of lead‐time variability by means of numerical examples and by marginal analysis. Having established that it is essential to consider lead‐time variability, we take advantage of theoretical developments and show how to calculate reorder points and safety stocks in some common situations.It is important to use the proper form for the compound distribution of demand during lead time. A normal approximation to it will often yield significant errors. This is because the true distribution is usually very much skewed to the right.
The use of cost‐based priorities in random and flow shops
Authors: Scudder Gary D. , Hoffmann Thomas R. 
Published: October 2002

AbstractThis article evaluates the use of cost information for establishing priorities in a job shop. Most traditional research in the area of job shop scheduling uses only time‐oriented rules and performance criteria when in reality, minimizing total cost is the most appropriate objective.Utilizing a simulation model of randomly‐routed and flow job shops, several priority rules are evaluated on the basis of time performance, primarily on‐time completions, as well as on the basis of cost performance: the minimization of work‐in‐process (WIP) investment. The priority rules use either time information only, cost or value information only, or both types of information in a composite manner. An additional concept examined is that of the speed of a job relative to its due date. Speed is examined for different profitability classes of jobs: high, medium, and low. It is often important that high profit jobs are completed on time, while low profit jobs may not be as critical.The priority rules are simulated at four utilization levels and several replications are made to make statements about the statistical significance of the results. The results show that a time rule, such as critical ratio, performs poorly on cost measures, moves high and low profit jobs indiscriminately, and completes significantly fewer jobs on time at high utilization levels than the cost rules examined. One of the cost rules that utilizes the value added to a job is the best performer in terms of cost and does quite well in completing jobs on time.
Yield management: A tool for capacity‐considered service firms
Authors: Kimes Sheryl E. 
Published: October 2002

AbstractAirlines typically sell their seats for a variety of different fares. If customers make reservations early, low fares might be available, but if customers call at the last minute, they will probably have to pay the full fare. Since deregulation, early all airlines have been using a technique called yield management. Yield management allows the airlines to allocate their fixed capacity of seats in the most profitable manner possible. Since the airline's inventory of seats is perishable, the airlines must have a method of quickly and accurately allocating potential demand to capacity. The airline industry has been in the forefront of using management, but yield management has potential application to any firm constrained by capacity. Other services which have adopted yield management include the lodging, rental car, delivery service, rail and cruise line industries.The objective of yield management is to maximize the revenue or yield of the firm. A good yield management system will help the firm decide how much of each type of inventory (whether it be seats on an airplane, rooms in a hotel, or cars in a rental car fleet) to allocate to different types of demand. This article attempts to structure the concept of yield management by reviewing current literature, classifying types of solution approaches, discussing the managerial implications of yield management and presenting a future research agenda. While corporate research on yield management has been performed, most firms are understandably reluctant to share the results of their research with others. Operations management researchers could assist small and medium sized capacity‐constrained firms by developing simple and accurate yield management techniques. The intent of the paper is to focus attention n the yield management and stimulate practical and theoretical research in this area.
Time and product variety competition in the book distribution industry
Authors: Lindsley William B. , Blackburn Joseph D. , Elrod Terry 
Published: October 2002

AbstractProduct variety and time have emerged as prominent dimensions in global competition. Marketers have emphasized the strategic advantages accruing from offering increased variety: on the other hand, operations managers have stressed reduced operations cycle times and faster response times to customer needs. Although substantial documentation supports the impact of such activities on costs, the only empirical evidence concerning actual rewards in the marketplace from such strategic endeavors is anecdotal.This study of the book distribution industry demonstrates a two‐phase methodology for valuing the rewards from faster response and improved variety. First an industry analysis was conducted to determine at a macro level how time and variety have been treated strategically and how it has affected the industry. The conclusion was that the very existence of the industry depends on the ability of these firms to offer a greater variety of titles shipped in smaller quantities in a relatively rapid fashion. Within the industry, those who can do this best have increased their market share substantially.To quantify the potential rewards accruing to time‐based and variety‐based strategies, conjoint (or trade‐off) analyses were conducted via telephone to estimate the specific trade‐offs that retailers were willing to make among price, delivery time, and product variety. By understanding the relative value of different services or attributes to the consumer (in this case the book retailer), the impact of changing these services by either the firm or one of its competitors can be evaluated. For example, in our study, to overcome retailer's loyalty to a competitor, distributors would need to deliver one day faster than the average and fill about 3% more of the retailer's title needs. Similarly, one can determine what order fill rate increase or delivery time reduction would be necessary to offset a specific price increase and not lose customers.In conclusion, the empirical research confirms the importance of time and variety as critical strategic dimensions. The emergence of a distributor that distinguishes itself from the competition along one or both these dimensions can alter the structure of the industry. Consequently, managers need to be cognizant of the relative values of time and variety in configuring their distribution strategy.
A systematic simulation approach for the design of JIT manufacturing systems
Authors: Abdou G. , Dutta S.P. 
Published: October 2002

AbstractThe paper provides a simulation model for kanban‐based scheduling in a multi‐stage, multi‐product manufacturing system. The model assists managers in determining the number of circulating kanbans and the corresponding container capacity. Each part is analyzed separately to find the optimum interarrivai time of the material handler, the optimum container capacity and the optimum number of kanbans. The analysis is based on the relationships between the overall cost and interarrivai times of each of these three input variables. Possible combinations of lot sizes are also investigated with the objective of reducing the number of such mixes. The results are used as an input for the multi‐product multistage simulation model to determine the best policy of mixed container capacities and number of kanbans. It is demonstrated that, given a set of operational conditions, a better design of a just‐in‐time manufacturing system can be attained through the application of the proposed simulation model.
A resource dependence perspective of Just‐in‐Time purchasing
Authors: Handfield Robert B. 
Published: October 2002

AbstractA substantial body of literature in operations management has emphasized the importance of establishing “Just‐in‐Time” (JIT) purchasing with suppliers in order to reduce inventory levels, reduce inspection and produce better products. This issue is paralleled in resource dependence theory, which predicts how organizations respond to uncertainty within their external environment. The current research proposes a model which uses resource dependence to explain how and why purchasing is moving towards JIT, thereby bridging the fields of operations management and organization theory. The model proposes that supply base reduction is a response to increased uncertainty in demand and that JIT is preceded by greater information sharing with fewer suppliers. Further, the success of JIT purchasing systems is sustained through reduced transaction uncertainty with critical suppliers. These hypotheses are embodied in a path analysis model, which is tested for the existence of causal linkages between the constructs. The path model was tested using data collected from interviews with production, purchasing and engineering personnel at forty Make‐to‐Order manufacturing facilities. The results of the study support the idea that purchasing departments in Make‐to‐Order firms are likely to reduce the number of critical suppliers in response to uncertainty in demand. Further, evidence of the relationship between information sharing and supply base reduction was established and information sharing was shown to be an antecedent to JIT purchasing. The hypothesis that supply base reduction is an antecedent to JIT was not supported. However, the results suggest that the two policies are complementary, in that a coordinated program of both JIT purchasing and supply base consolidation can lead to significant reductions in transaction uncertainty
The effects of lot sizing and dispatching on customer service in an MRP environment
Authors: Gardiner Stanley C. , Blackstone John H. 
Published: October 2002

AbstractResults are presented of a simulation analysis of a hypothetical fabrication and assembly shop controlled by material requirements planning. The purpose of the study is to investigate the impact of lot sizing on the customer service performance of dispatching techniques in an MRP‐controlled assembly job shop operating near capacity. Six dispatching techniques are compared based on the tardiness of customer orders under four lot‐sizing techniques, two levels of demand, and two levels of nervousness. The study is conducted with a stable product mix, limited production capacity, and fixed routings. Random shifts in short‐term product mix cause short‐term bottlenecks, but one of the 15 work stations has less than 10% idle time and is the most commonly encountered bottleneck.The interaction of lot‐sizing and dispatching techniques was found to be a function of capacity utilization, a factor influenced by demand and nervousness level. Under low demand, earliest job due date yielded the best performance with regard to the percentage of tardy orders, average order tardiness, and maximum order tardiness. Under high demand, earliest job due date performed best with respect to average order tardiness and maximum order tardiness, but the best dispatching technique with respect to percentage of tardy orders depended on the lot‐sizing technique and the nervous‐ness level. Under high demand and high nervousness, effective capacity decreased and queues increased with economic order quantity, period order quantity, or least total cost. Economic order quantity generated the smallest batches. Period order quantity and least total cost generated extra set‐ups under high nervousness. Use of either of the three lot‐sizing techniques at high demand and high nervousness forced a choice between a dispatching technique that yields a low percentage of orders tardy (earliest modified operation due date) and one that generates low maximum order tardiness (earliest job due date). The Silver‐Meal heuristic consumed less effective capacity than the other lot‐sizing techniques. Using Silver‐Meal at high demand and nervousness, earliest job due date performed best with respect to each tardiness measure.The bottleneck causes the plant to behave like a single machine shop. Since large queues are maintained at the bottleneck, that is where the choice of dispatching technique is critical. Earliest due date minimizes the percentage of tardy orders. Earliest modified operation due date, operating like the shortest processing time rule, minimizes the percentage of tardy orders, but maximum tardiness is high. These results may stimulate new interest in single‐machine scheduling.The combination of least total cost and earliest job due produced the best overall performance at low demand. At high demand, Silver‐Meal and earliest job due date achieved the best performance.