This research focuses on the planning and scheduling challenges that component manufacturers encounter in the high-tech industry. Positioned between finished goods manufacturers and suppliers, component manufacturers experience special requirements from a scheduling perspective, e.g. material availability and production capability must be simultaneously addressed in the optimization logic, Available To Promise (ATP) and Capable To Promise (CTP) mechanisms have to be achieved with high accuracy, and etc. After reviewing the component manufacturers' planning needs, this research proposes an advanced planning and scheduling framework that covers forecasting, master production scheduling, detail scheduling and order fulfillment. Also, attention has been focused on scheduling area by developing two improved Lagrangean relaxation methods that are able to satisfy the special requirements. One of the improved methods embeds the material availability constraint, thereby changing the existing Lagrangean relaxation method from solving sub-problems to list scheduling. The other method uses a new heuristics rule to consider material availability during list scheduling. A realistic rolling scheduling environment is prepared and a variety of random cases are examined in order to test the efficiency of the methods. The experimental results are then compared to those for the existing Lagrangean relaxation method. Different aspects, such as the estimated and actual production lead-times, the total number and tardiness of delayed jobs are analyzed. These results can be used to indicate the accuracy of the customer commitment for each of the different methods. The improved Lagrangean relaxation method that embeds the material availability in the constraints generates the most accurate scheduling result. Moreover, the Lagrangean relaxation method also exhibits robustness in a rolling scheduling environment. Based on the experimental results, the proposed planning and scheduling framework should be able to satisfy component manufacturers' planning requirements.

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In this paper the Discrete Lotsizing and Scheduling Problem (DLSP) on identical parallel machines with setup times is considered. The problem is determining the sequence and size of production batches for multiple items. The objective is to find a minimal cost production schedule such that deterministic, dynamic demand is fulfilled with backlogging. The problem is formulated as an integer programming problem and reformulated as a Generalized Set Partitioning Problem (GSPP). We show that a problem which checks optimality of LP relaxation problem of GSPP is equivalent to a single item, namely, a discrete lotsizing scheduling problem on parallel machines. It means that GSPP is decomposed to subproblems, and each one is solvable with dynamic programming. We obtain the lower bound of the reformulated problem by solving a LP relaxation problem of GSPP optimally and present a column generation heuristic to solve GSPP, which optimizes the restricted GSSP composed with columns generated at that time. The quality of the solutions can be measured, since the heuristic generates both lower and upper bounds. We compare our algorithm and a heuristic based on Lagrangian relaxation proposed by Campbell. Computational results on a personal computer show that our heuristic is rather effective in terms of quality of the solutions. One of the advantages of the column generation method is that the setting of parameters is not required in contrast to Lagrange relaxation.

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The NIOSH equation was formulated to evaluate lifting and lowering tasks with respect to given conditions such as the load being handled, displacement from the origin to destination and other factors. On the other hand, the OWAS method is a widely applied method in the analysis and improvement of working posture. It should be noted that working posture plays a key role in material handling. When using the NIOSH equation and OWAS method, data from actual observations have to be gathered before any improvements can be made. However, this research proposes a method based on the application principles of the NIOSH equation and OWAS method, to generate improvement ideas even before any material handling tasks are carried out. This suggests that if vital information such as the size (dimension, weight) of the load, its position and displacement with respect to the worker from start to end of material handling tasks, layout, material handling process and equipment etc. are known, then the corresponding work posture can be determined. Therefore, if the necessary information on the working conditions is known before the work is done, it is possible to predict the working posture. In addition, not only the working posture can be predicted but also the work posture changes, dangers and underlying hazards. This study examines the predicted working posture through the use of a human body model. Nine basic posture patterns are designed to emulate the elements of material handling tasks. Using a formula, working posture changes are obtained from joint angle changes of the human body model expressed in a polynomial. Then, the working posture is analyzed through the use of posture and action codes of the OWAS method. From the mathematical computation, using a material handling example of a human model, the procedure of formulating the OWAS posture and action codes is shown.

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The current investigation identifies the means of setting up a theoretical safety stock and determines the order point in an ordering point system that includes the distribution of lead times. In actual inventory control, changing the lead time does occur and is not considered a fixed value. However, for a conventional investigation in which the lead time is treated as fixed, a large change in lead time may result in excessive safety stock, causing increased inventory problems. A change in lead time, which can be described by a discrete probability distribution, can be incorporated into a theoretical computation of safety stock by including the change in quantity demanded. A direct calculation of standard deviation is proposed, and the effective range is checked by numerical simulation. In the current investigation, the numerical simulation showed the following : (1) The proposed safety stock that satisfies the theoretical modulus of allowance deficiency has been established; (2) The proposed form cuts inventory cost performance, as compared with the conventional form; and, (3) The proposed form makes smaller inventory changes than the conventional form/operative. The above shows that the proposed form was effective in determining the safety stock in the event of a changing lead time, and for the calculation of an order point. The significance of computing a theoretical safety stock for the conditions of a changing lead time and the value of an estimated order point are as follows : (1) The excess inventory drawback for the safety stock estimate calculated by conventional form when there is a large change in lead time was improved; (2) Effectively sets a target for a shortened lead time, because in many cases a shortened lead time is difficult to attain; and, (3) By preparing for dynamic lead times, cuts in the inventory cost performance, such as average propensity to save, can be enlarged.

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Recently, interest in logistics and supply chain management has grown explosively through exposure to fierce competition and changing circumstances. This interest has led many companies to build their supply chain. In most cases, however, organizational constraints impede their formation of supply chain management (SCM). To breakthrough these constraints, various kinds of scorecards have been developed. A scorecard is a simplified benchmark methodology to diagnose and evaluate various advantages and disadvantages of business operations, such as IT utilization, etc. from the point of total optimization of SCM. In this study, we propose and develop the general-purpose scorecard named the SCM logistics scorecard (LSC) after conducting survey research on various scorecards, and verify its validity and effectiveness. To do this, we gather actual data based on LSC from many manufacturing companies and extract five factors, which represent the drivers of managerial performance through these data. Using the corresponding companies' financial bottom line indexes, we analyze the correlation between these indexes and our factors. The result shows that higher scores of LSC, which leads to higher scores in the five factors, bring significantly positive financial outcomes. At the same time, we also verify statistically that IT itself is just an enabler or means in building SCM by introducing a causal-effect model among these factors leading to managerial performances.

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Kanban system as a pull system has been the center of attention on inventory and WIP reduction for many years. Since the pull system could be applied only to repetitive type of production, it should be meaningful if some scheduling method could attain the same WIP level with the pull system's performance. Scheduling is a universal method both for repetitive and non-repetitive production. Therefore, the scheduling method becomes effective to get shorter total lead time for non-repetitive production environment such as a Make-To-Order type factory which has long multiple processes. This paper shows how the FCS (Finite Capacity Scheduling) system is applied for getting the same production instructions and WIP results with the case of using "one-card system" which is one of the typical pull systems. The comparison is done under the conditions of a certain demand model between a one-card system and an event-based FCS with backward pass. The outcome of the hand simulation shows that each WIP between processes is converged to the same volume with the case of using the pull system. Although FCS could not overcome the pull system in the aspect of WIP reduction, a market-based production system where materials move only if there is a demand for it would be realized in any production environment by utilizing a scheduling system. Most Make-To-Order type factories, which have long multiple processes have used a preplanning-based system so far. However, the system could be more demand-pull system by adopting the FCS system. To make sure, the scheduling system should not be considered as a planning system. Rather, it is an information system to transmit the customers' requirements.

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