A NOTE ON LEARNING CURVE PARAMETERS

This note describes differences in the feasible range of values that the learning curve parameter may take when a unit learning approach is used as opposed to a cumulative-average learning curve. Clarification of this point is important because learning curve theory now is used in a variety of areas.     

A DISCRETE DYNAMIC OPTIMIZATION MODEL FOR MADE-TO-ORDER COST ANALYSIS

A model is presented that yields optimal production rates for a firm producing a contracted order. The model is unique in that it considers the influence of production rate and learning on total program cost. An application to the specific characteristics of two military production programs is presented. As demonstrated by the application, models of this type may be used as decision-making tools when negotiating the cost impact of contract modifications.     

A COMPARISON OF SEQUENCING RULES FOR A TWO-STATE HYBRID FLOW SHOP

A common manufacturing environment in many industries (such as the glass, steel, paper, costume jewelry, and textile industries) is a hybrid flow shop. This system has continuous-process machinery in the fist state of manufacturing and repetitive-batch equipment in the second. Little research has investigated this type system. Scheduling managers of hybrid flow shops tend either to use existing job-shop rules or to devise their own rules. These approaches often are less than adequate for efficient scheduling. In this paper we extend the rule presented by Narasimhan and Panwalker [4] to include a general class of hybrid flow shops. This extenstion, called the generalized cumulative minimum-deviation (GCMD) rule, is compared under various operation conditions to three other sequencing rules: shortest processing time, longest processing time, and minimum deviation. The operating conditions are determined by the number of machines at both stages. The results of 7200 simulation runs demonstrate that the GCMD rule is better than the other rules in minimizing each of five chosen criteria. Thus, the GCMD rule can help managers to schedule hybrid flow shops efficiently to achieve various corporate objectives.     

MODELING LEARNING CURVE AND LEARNING COMPLEMENTARITY FOR RESOURCE ALLOCATION AND PRODUCTION SCHEDULING*

Research on learning effects in mathematical programming models for optimum resource allocation has called attention to the difficulty in solving such models in their original nonlinear form. In this paper, systematically varying sizes of linear segments are designed to approximate productivity changes along the learning curve, and a single separable linear programming model is developed. With production complementarity and learning transmission between products, a more realistic resource allocation and production scheduling problem emerges. Two cases of learning transmissions are considered, and the model design process, which defines a decision problem that can be solved by a simplex algorithm, is demonstrated.     

A SYSTEMS PERSPECTIVE ON MATERIAL REQUIREMENTS PLANNING*

For many companies, the implementation of material requirements planning systems has failed to produce the expected improvements in manufacturing efficiency. This paper shows that MRP failure can occur in the common situation in which MRP is installed in a manufacturing environment that has evolved around manual methods of material control. A system dynamics simulation model is used to interrelate decision functions (policies) of a manufacturing firm. Simulation runs of the model operating with manual methods of material control show six- to seven-year fluctuations in production, ordering, and labor. A modified version of the model, changed only by the introduction of a requirements explosion to represent MRP, shows that MRP can actually cause more severe production fluctuations, resulting in lower average labor productivity and higher manufacturing costs. The major practical implication of the analysis is that the organizational environment that suits MRP (and utilizes its inherent strengths) is different from the environment that is likely to prevail at the time of implementation.     

THE IMPACT OF EXTREME OBSERVATIONS ON SIMPLE FORECASTING METHODS*

In general linear modeling, an alternative to the method of least squares (LS) is the least absolute deviations (LAD) procedure. Although LS is more widely used, the LAD approach yields better estimates in the presence of outliers. In this paper, we examine the performance of LAD estimators for the parameters of the first-order autoregressive model in the presence of outliers. A simulation study compared these estimates with those given by LS. The general conclusion is that LAD does not deal successfully with additive outliers. A simple procedure is proposed which allows exception reporting when outliers occur.     

SOCIAL LEARNING THEORY AND THE IMPLEMENTATION OF PRODUCTION INNOVATION*

In a study of the implementation of production innovation using a social learning theory focus, four organizations were monitored with a real-time study design. The following propositions were strongly supported: (1) During the initial implementation period (3–4 months), the stress felt by personnel in new user organizations was significantly higher (p < .01) than for organizations previously experienced with technology; (2) Firms experienced with the new technology obtain early success when compared with inexperienced firms (p < .01). Moderate support was found for the proposition that new users rely heavily on original equipment manufacturers for demonstration to acquire new skills, but gradually models within the user organization emerge as the dominant influence. The proposition that new users have significantly higher imitation scores than users experienced with the technology was only weakly supported. No substantive or significant changes in the attitudes of users toward the innovation were found during the first three to four months of the implementation period. These and other results suggest that longitudinal studies of this type ought to be carried out over periods in excess of 2 1/2 years. Implications for the management of change are presented.     

A SIMULATION ANALYSIS OF THE JAPANESE JUST-IN-TIME TECHNIQUE (WITH KANBANS) FOR A MULTILINE,MULTISTAGE PRODUCTION SYSTEM

The Japanese “just-in-time with kanban” technique reduces in-process inventory to absolute minimal levels, in concert with the Japanese belief that inventory is an unnecessary evil. Due to the success of Japanese firms that employ this type of system, American firms would like to import this technique and emulate Japanese successes. But this Japanese success may be attributable not only to the just-in-time with kanban technique but also to the production environment in which the technique is employed. This paper simulates the just-in-time with kanban technique for a multiline, multistage production system in order to determine its adaptability to an American production environment that might include such characteristics as variable processing times, variable master production scheduling, and imbalances between production stages. The results have practical implications for those firms considering adoption of the Japanese technique.     

REQUIREMENTS PLANNING FOR CONTROL OF INFORMATION RESOURCES

Producing reports assembled from files, records, and raw data is a major function of the computer in modern organizations. Transaction processing, records management, file organization, and data-base management are aspects of the information production function that have received a good deal of attention. But planning, scheduling, and controlling the production of information products have been neglected. For complex applications involving assembly of reports from multilevel information sources, the requirements planning model is suggested as an effective alternative to present methods. Thus, our suggestion is that the computer be used to plan, schedule, and control computer production of information products. Presently available material requirements planning software may be employed with minor modifications that depend on the given information system characteristics. In this paper an example of requirements planning as applied to production of information in a satellite control system is presented.     

A DISCRETE PRODUCTION SWITCHING RULE FOR AGGREGATE PLANNING

Aggregate planning (AP) is a necessary activity for manufacturing and services alike. A shift toward high-volume batch and continuous flow processes within American manufacturing has given rise to increasing numbers of crew-loaded facilities. A majority of AP approaches incorporate continuous decision variables and require frequent adjustments to both production and work-force settings. Despite the availability and diversity of these approaches, few significant applications have been reported. This paper presents the detailed development of a discrete AP switching rule that can be applied to a variety of cost environments. Inventory costs are estimated using an interval approach rather than traditional point estimates. The model allows incorporation of overtime options and is interactive in nature. Decision variables from the model can be disaggregated and linked directly to lower-level planning activities. Actual results of model implementation are reported. An overview of the model's incorporation into the larger context of hierarchical production planning is found in [21].     

A Simulation Study of Sequencing Rules in a Kanban-Controlled Flow Shop*

This paper addresses the problem of sequencing in decentralized kanban-controlled flow shops. The kanban production control system considered uses two card types and a constant withdrawal period. The flow shops are decentralized in the sense that sequencing decisions are made at the local workstation level rather than by a centralized scheduling system. Further, there are no material requirements planning (MRP)-generated due dates available to drive dispatching rules such as earliest due date, slack, and critical ratio. Local sequencing rules suitable for the decentralized kanban production-control environment are proposed and tested in a simulation experiment. These rules are designed so that they can be implemented with only the information available at the workstation level. Example sequencing problems are used to show why the shortest processing time rule minimizes neither average work-in-process inventory nor average finished-goods withdrawal kanban waiting time. Further, it is shown how work station supervisors can use the withdrawal period, in addition to the number of kanbans, to manage work-in-process inventories.     

A COMPARISON OF INVESTMENT ALLOCATION STRATEGIES FOR DISTRIBUTION INVENTORIES

Management goals in distribution inventories are often expressed in terms of the maximum percentage of aggregate sales that should be back ordered. This paper compares several strategies for allocating total inventory investment to each item stocked in order to meet such goals. Computational results are given from a wholesale distribution inventory. The results show that multi-item strategies (which consider the interactions between items) require substantially less investment to meet management goals than strategies that treat each line item independently. All models in this research are approximations based on the assumptions commonly used in practice.     

PROCEDURES FOR DETERMINING RELATIVE FREQUENCIES OF PRODUCTION/ORDER IN MULTISTAGE ASSEMBLY SYSTEMS*

We show that the problems of determination lot sizes in a multistage assembly system for the case of instantaneous production and constant demand for the end item can be reduced to the problems of determining relative frequenceis of production/order for items at each production stage. We further show that such frequencies are independent of the demand levels. Optimal and near-optimal solution procedures for this reduced problem are provided. The near-optimal procedure successively treats each stage of production as a final production stage while simulatenously incorporating decisions made at lower stages into decisions made at higher stages. Experimental results show that the near-optimal procedure results in optimal solutions 75 percent of the time and performs considerably better than representative heuristics available in the literature. Further, its performance is relatively less susceptible to product/structural characteristics of the system.     

“A JOINT ECONOMIC-LOT-SIZE MODEL FOR PURCHASER AND VENDOR”: A COMMENT*

Banerjee [1] developed a joint economic-lot-size model for the case where a vendor produces to order for a purchaser on a lot-for-lot basis under deterministic conditions. The assumption of lot-for-lot bases is restrictive in nature. In this note, a more general joint economic-lot-size model is suggested and it is shown to provide a lower or equal joint total relevant cost as compared to the model of Banerjee.     

DUAL-RESOURCE PARALLEL QUEUES WITH SERVER TRANSFER AND INFORMATION ACCESS DELAYS*

Dual-resource constrained queuing systems contain fewer servers than service facilities. This study uses computer simulation to evaluate several server assignment procedures in a dual-resource system. A field study serves as the basis for developing a model with two service facilities in parallel, a single server, and deterministic information access and transfer delays that can be applied to job shops, computer operating systems, and elevators. Several findings, useful in server assignment decision making, resulted from the study. If first-come, first-served sequencing is used, delaying server assignment at a facility until all jobs are completed reduces both the mean and the variance of job flow time. If shortest-process-time-first sequencing is used, an assignment rule is tested that delays a server at a facility until a sufficiently short job is estimated to have arrived elsewhere. This rule performs best overall in terms of both the mean and variance of flow time. Methods to implement this decision rule easily are discussed.     

Applications and Implementation: AN EXPERIMENTAL COMPARISON OF CELLULAR (GROUP TECHNOLOGY) LAYOUT WITH PROCESS LAYOUT

This study compares different strategies for arranging machines in a facility. Computer simulation of two different machine shops was used to compare process layout (the arrangement of groups of machines where the machines within a group are interchangeable) to cellular layout designed using group technology concepts (the use of manufacturing cells where each cell contains different types of machines dedicated to the production of similar parts). Four layout strategies, including process layout, cellular layout, and two hybrid layouts, were compared in two machine-shop models. The shops that used cellular layouts had shorter setup times, lower machine utilization, and shorter distances traveled, on average. The shops with process layout, however, had better performance on queue-related statistics such as work-in-process inventory level and average flow time. This suggests that a well-organized traditional job shop may be able to achieve overall performance that at least is comparable to that of the same shop using cellular (group technology) layout.     

THE CLASSIC ECONOMIC PRODUCTION QUANTITY MODEL WITH SETUP COST AS A FUNCTION OF CAPITAL EXPENDITURE*

The formulation of the classic economic production quantity (EPQ) model is extended to include setup cost as a function of capital expense. Additional capital will buy reduced setup cost. Thus, the objective now is to balance holding, setup, and capital expenses. This new formulation is solved under conditions where setup cost varies exponentially and linearly as a function of capital expense. Decision rules are formulated to indicate under what conditions setup cost reduction reduces total cost. For the linear function, it is shown that once the decision to reduce setup cost is justified, the optimal choice is the minimum setup cost that is technologically feasible.     

PRODUCT STRUCTURE COMPLEXITY AND MULTILEVEL LOT SIZING USING ALTERNATIVE COSTING POLICIES*

This research evaluates the effect of product structure complexity on the performance of several lot-sizing procedures in a multilevel manufacturing environment. The experiment compares two different costing policies, full value added (FVA) and marginal value added (MVA), for calculating inventory holding cost. The major finding of the research is that product structure complexity has very little effect on the performance of various lot-sizing procedures. A second finding is that when product structures with varying components per parent and stocking points for a particular end item are present, the MVA costing policy emerges as the policy of choice because it favors slightly the Silver-Meal (SM)/least-total-cost (LTC) procedures over the Wagner-Whitin (WW)/LTC procedures.     

An Investigation of Scheduling Policies in a Dual-Constrained Manufacturing Cell*

In previous group scheduling studies, labor has essentially been ignored by assuming that enough labor is assigned to each machine in the cell. In reality, however, management usually does not have the resources to employ a laborer at each machine in the cell (i.e., machines need to share labor). Both labor scheduling and group scheduling heuristics need to be administered to manage the cell effectively. This study develops and examines scheduling procedures for a dual-constrained (i.e., machine and labor) manufacturing cell. Eleven decision rules are developed and tested under 16 different experimental conditions. The experimental factors used are interarrival time distribution, cell load, setup-to-run-time ratio, and transfer-to-run-time ratio. Results show that interarrival time distribution and cell load have the greatest impact on the performance of the cell. This suggests that effective production planning aimed at reducing job arrival variation and leveling the cell load can substantially improve cell performance. Among the experimental factors, setup and transfer-to-run-time ratio factors had the strongest influence on the rankings of the decision rules. These rankings were fairly robust across all experimental conditions and performance measures. The results also indicated that the inclusion of labor as a contraint in the cell had a significant impact on the performance of several group scheduling heuristics. Finally, it was shown that the best performing decision rules consider both transfer time and subfamily setup times.