The machine-part group formation is to group the sets of parts having similar processing requirements into part families, and the sets of machines needed to process a particular part family into machine cells using grid computing. It forms machine cells from the machine-part incidence matrix by means of Self-Organizing Maps(SOM) whose output layer is one-dimension and the number of output nodes is the twice as many as the number of input nodes in order to spread out the machine vectors. It generates machine-part group which are assigned to machine cells by means of the number of bottleneck machine with processing part. The proposed algorithm was tested on well-known machine-part grouping problems. The results of this computational study demonstrate the superiority of the proposed algorithm.

The purpose of this study was to investigate the effects of sleep/wake behavior for shift workers in the iron and steel industry using wrist actigraph for 59 male workers on a continuous full-day three-team three-shift system of backward rotation including on-duty and off-duty periods. The wrist actigraph data were recorded for 15 days (l shift cycle) for each subject. The sleep length at home during night shift decreased significantly as compared to the morning or evening shifts. The night shift nap length increased significantly in all sections as compared to the morning or evening shifts. The nap length in the Steel Manufacturing Process and Rolling Process during night shift decreased significantly as compared to the Machine Maintenance Section, the Forwarding of Products Section, and the Field Management Section. However, the sleep length at home while off-duty period increased significantly. The percentage of nap length during night shift in the Rolling Process, Steel Manufacture Process, and the other three types of jobs was 16.0%, 20.4%, and about 50.0%, respectively. The nap length during night shift for the above 50 year olds increased significantly as compared to the below 50 year olds. Finally, we discussed the role of nap-taking during the burden on night shift workers and the increased difficulty in continuing their job.

In this paper, we address a layout design problem, PTL[3], for determining an optimal 3-class-based dedicated linear storage layout in a class of unit load storage systems. Our objective is to minimize the expected single command travel time. We analyze PTL[3] to derive a fundamental property that an optimal solution to PTL[3] is one of the partitions based on the PAI(product activity index)-nonincreasing ordering. Using the property and partial enumeration, we construct an efficient exact algorithm with O $(n\;{\lceil}\;log\;n\;{\rceil}\;)$ for solving PTL[3].

This paper deals with a supply chain with a company and its contractor that produces products by the OEM contract with the company. The supply chain of interest has two distinct features. First, the company is the supplier of raw material required in the production at the contractor. Second, the company and its contractor make a delivery shipment arrangement that the replenishment lead time is determined depending on demand process. We show that the optimal inventory policy is monotonically changed as either the replenishment setup cost or inventory holding cost becomes increased or decreased. We also present asymptotic properties of the optimal inventory policy when either the number of outstanding customer orders or the inventory level becomes very large.

This paper proposes the variables repetitive group sampling plan where the quality characteristic following normal distribution has upper or lower specification limit. The problem is formulated as a non-linear programming problem where the objective function to minimize is the average sample number and the constraints are related to lot acceptance probabilities at acceptable quality level (AQL) and limiting quality level (LQL) under the operating characteristic curve. Sampling plan tables are constructed for the selection of parameters indexed by AQL and LQL in the cases of known standard deviation and unknown standard deviation. It is shown that the proposed sampling plan significantly reduces the average sample number as compared with the single or the double sampling plan.

We consider the traffic grooming problem for the design of SONET/WDM(Synchronous Optical NETwork/Wavelength Division Multiplexing) ring networks. Given a physical network with ring topology and a set of traffic demands between pairs of nodes, we are to obtain a stack of rings with the objective of minimizing the number of ADMs installed at the nodes. This problem arises when a single ring capacity is not large enough to accommodate all the demands. As a solution method, an efficient algorithm based on the branch-and-price approach has been reported in the literature for the problem in which only unidirecional path switched ring (UPSR) was considered. In this study, we suggest integer programming models and the algorithms based on the same approach as the above one, considering two-fiber bidirectional line switched ring(BLSR/2), and BLSR/4 additionally. Using the results, we compare the number of required ADMs for all types of the ring architecture.

Supply chain management(SCM) has been recognized as a major strategy in today's market place. A growing number of researchers have begun to realize the strategic importance of model construction, planning, controlling and operation for SCM. Also various researches of supply chain model building are going on. In this paper, we synthesis key elements of supply chain model such as performance factors, decision variables and constraints. We have reviewed past and present supply chain models and then analyzed those in view of environment factors, operations, solution approaches.

By committing to a long-term replenishment contract, suppliers can mitigate the pressure to find new customers and afford to charge a discounted price to buyers seeking to lower their purchasing costs. In this paper, we develop an analytical model from buyer's perspective for the contracting process to investigate the buyer-supplier interactions. Based on the developed model, we propose an algorithm to derive optimal strategy for the contract. We consider a system with a single buyer and a supplier in a situation where the buyer's inventory is controlled by (R, S) policy under VMI setting. According to the contract, the supplier should replenish the buyer's inventory up to a fixed level every R times during a specified period. The buyer purchases any deficient amount from a spot market at a higher price. We show by computational experiment that our proposed algorithm finds the global optimum solution.

This study considers a linear connected-(r,s)-out-of-(m,n):F lattice system whose components are ordered like the elements of a linear (m,n )-matrix. We assume that all components are in the state 1 (operating) or 0 (failed) and identical and s-independent. The system fails whenever at least one connected (r,s)-submatrix of failed components occurs. The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unit time. To find the optimal threshold of maintenance intervention, we use a genetic algorithm for the cost optimization procedure. The expected cost per unit time is obtained by Monte Carlo simulation. The sensitivity analysis to the different cost parameters has also been made.