Recently, the amount of heat generated in devices has been increasing due to the miniaturization and high performance of electronic devices. Cu-graphite composites are emerging as a heat sink material, but its capability is limited due to the weak interface bonding between the two materials. To overcome these problems, Cu nanoparticles were deposited on a graphite flake surface by electroless plating to increase the interfacial bonds between Cu and graphite, and then composite materials were consolidated by spark plasma sintering. The Cu content was varied from 20 wt.% to 60 wt.% to investigate the effect of the graphite fraction and microstructure on thermal conductivity of the Cu-graphite composites. The highest thermal conductivity of 692 W m−1K−1 was achieved for the composite with 40 wt.% Cu. The measured coefficients of thermal expansion of the composites ranged from 5.36 × 10−6 to 3.06 × 10−6 K−1. We anticipate that the Cu-graphite composites have remarkable potential for heat dissipation applications in energy storage and electronics owing to their high thermal conductivity and low thermal expansion coefficient.

Fair Allocation of profits or costs arising from joint participation by multiple individuals or entities with different purposes is essential for their continuing involvement and for their dissatisfaction reduction. In this research, fair allocation of the profits of forming a grand coalition in Three-Echelon Supply Chain (TESC) game that is composed of manufacturer, distributor and retailer, is studied. In particular, the solutions of the proportional method of profit, the proportional method of marginal profit, and Shapley value based on cooperative game theory are proved to be in the desirable characteristics of the core. The proportional method of profit and the proportional method of marginal profit are often used because of their ease of application. These methods distribute total profit in proportion to profits or marginal profits of each game participant. In addition, Shapley value can be defined as the average marginal profit when one game player is added at a time. Even though the calculation of the average of all possible marginal profits is not simple, Shapley value are often used as a useful method. Experiments have shown that the solution of the incremental method, which calculates the marginal cost of adding game players in the order of manufacturers, distributors and retailers, does not exist in the core.

High variance observed in the measurement system can cause high process variation that can affect process capability badly. Therefore, measurement system analysis is closely related to process capability analysis. Generally, the evaluation for measurement system and process variance is performed separately in the industry. That is, the measurement system analysis is implemented before process monitoring, process capability and process performance analysis even though these analyses are closely related. This paper presents the effective concurrent evaluation procedure for measurement system analysis and process capability analysis using the table that contains Process Performance (Pp), Gage Repeatability & Reproducibility (%R&R) and Number of Distinct Categories (NDC). Furthermore, the long-term process capability index (Pp), which takes into account both gage variance and process variance, is used instead of the short-term process capability (Cp) considering only process variance. The long-term capability index can reflect well the relationship between the measurement system and process capability. The quality measurement and improvement guidelines by region scale are also described in detail. In conclusion, this research proposes the procedure that can execute the measurement system analysis and process capability analysis at the same time. The proposed procedure can contribute to reduction of the measurement staff’s effort and to improvement of accurate evaluation.

The cooperative game theory consists of a set of players and utility function that has positive values for a subset of players, called coalition, in the game. The purpose of cost allocation method is to allocate the relevant cost among game players in a fair and rational way. Therefore, cost allocation method based on cooperative game theory has been applied in many areas for fair and reasonable cost allocation. On the other hand, the desirable characteristics of the cost allocation method are Pareto optimality, rationality, and marginality. Pareto optimality means that costs are entirely paid by participating players. Rationality means that by joining the grand coalition, players do not pay more than they would if they chose to be part of any smaller coalition of players. Marginality means that players are charged at least enough to cover their marginal costs. If these characteristics are all met, the solution of cost allocation method exists in the core. In this study, proportional method is applied to EOQ inventory game and EPQ inventory game with shortage. Proportional method is a method that allocates costs proportionally to a certain allocator. This method has been applied to a variety of problems because of its convenience and simple calculations. However, depending on what the allocator is used for, the proportional method has a weakness that its solution may not exist in the core. Three allocators such as demand, marginal cost, and cost are considered. We prove that the solution of the proportional method to demand and the proportional method to marginal cost for EOQ game and EPQ game with shortage is in the core. The counterexample also shows that the solution of the proportional method to cost does not exist in the core.

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of gas energy consumption in an air handling unit. To this end, we consider the volatility of the time series and demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the gas consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the gas consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of “context units” in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the gas consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

Cost allocation studies on the rational allocation method for the common cost of the joint products or services that provide different benefits to each economic entity under the constraints of the efficiency and fairness. Cooperative game theory is often used for cost allocation and studies on a fair and efficient allocation of the utility if some feasible utility for a whole or subset of the players in a game is given. This study shows a variety of cooperative game theory approaches and discusses the pros and cons of each approach.

If the coalition of players orders the product together, then they can reduce the inventory costs such as ordering cost and holding cost. Inventory game can be defined as the allocation of the inventory costs to the players in a fair and rational manner. The characteristics recommended for the solutions provided by the method for the inventory game are completeness, rationality, and marginality. The solutions that satisfy these characteristics are in the core, where the proportional method may depend on the allocator. This study has found out that the solutions of the proportional method with some allocators for economic order quantity model exist in the core.

With the development of industrial technology and science, production and manufacturing facilities have been enhanced and improved, and the importance of the safety of workers has also been regulated and limited by various safety management methods. As a way to secure the safety of the workers from the production facility, the fail-safe and fool-proof methods are now being applied. Any possible insecure behavior and unsafe conditions can be removed by adopting the standards and specifications that are now secure the safety of workers and equipment. This research analyzes EN ISO 13849-1 international and European standards during CE certification. In order to secure acceptable reduced risks, the risk assessment process of ISO 12100 and the processes for reducing its risk are applied. In the current ISO 13849-1 standard, the criteria for the required performance level PLr (Required Performance Level) for the applicable risk and safety functions through the risk assessment are subjective and not subdivided. Therefore, the evaluation criteria are likely to cause judge’s judgement error due to qualitative judgement. This research focuses on evaluation and acceptable performance level setting for the safety circuit of the equipment. We propose an objective and specific evaluation criteria to secure safety, and the proposed evaluation criteria are applied to the case study of the safety circuit for the equipment. In order to secure the safety of the entire safety circuit, the improvement of the MTTFd and DC level related to the SRP/CS (Safety-Related Parts of Control Systems)’ lifetime is required for the future research.

Vendor Managed Inventory is a well-known vendor-retailer coordination approach in supply chain management where the vendor manages inventory of the retailer and determines the order interval and order quantity for the retailer. To consider practical situation, the upper limit of inventory for the retailer is set. If the inventory level for the retailer exceeds the upper limit, then the penalty cost is charged to the retailer. Furthermore, maximum allowable inventory level is set for the vendor to prevent the vendor from keeping much inventory. Single-vendor multi-retailer supply chain model with upper limit of inventory for vendor and retailers is studied. All the retailers’ are assumed to have the common cycle time, and a vendor manages retailers’ inventory and replenishes products. The mathematical formulation is introduced to minimize the total cost including the penalty cost violating the upper limit of inventory for retailers with the constraint of maximum allowable inventory level. The solution procedure based on Karush-Kuhn-Tucker (KKT) conditions is derived. KKT conditions are often applied to find an optimal solution of nonlinear programming problem with constraints. An illustrative example is used to show the application of the proposed solution procedure. Furthermore, sensitivity analysis is done to find out the relationship between maximum allowable inventory level and other values such as order quantity, the number of shipment, vendor’s cost, retailer’s cost, and total cost. As maximum allowable inventory level decreases, the number of shipment decreases but total cost increases. Order quantity has the trend of decline and is affected by the number of shipment.

Vendor Managed Inventory is a well-known vendor-retailer coordination approach in supply chain management. If the inventory level for the retailer exceeds the upper limit, then the penalty cost is charged to the retailer. Furthermore, maximum allowable inventory level is set for the vendor to prevent the vendor from keeping much inventory. Single-vendor multi-retailer supply chain model with upper limit of inventory for vendor and retailers is studied. All the retailers’ are assumed to have the common cycle time, and a vendor manages retailers’ inventory and replenishes products. The mathematical formulation is introduced to minimize the total cost including the penalty cost violating the upper limit of inventory for retailers with the constraint of maximum allowable inventory level. The solution procedure based on Karush-Kuhn-Tucker(KKT) conditions is derived.

Unlike most researches that focus on single manufacturer or single buyer, this research studies the cooperation policy for two participants of supply chain such as single vendor and single buyer. Especially, this paper deals with single vendor-single buyer integrated-production inventory problem. If the buyer orders products, then the vendor will start to make products and then the products will be shipped from the vendor to the buyer many times. The buyer is supposed to order again when the buyer’s inventory level hits reorder point during the last shipment and this cycle keeps repeated. The buyer uses continuous review inventory policy and customer’s demand is assumed to be probabilistic. The contribution of this paper is to present a mixed approach and derive its cost function. The existing policy assumes that the size of shipping batch from single vendor to single buyer is increasing, called Type 1, or constant, called Type 2. In mixed approach, the size of shipping batch is increasing at the beginning part of the cycle, and then its size is constant at the ending part of the cycle. The number of shipping for Type 1 and Type 2 in a cycle in mixed approach is determined to minimize total cost. The relationship between parameters, for example, the holding cost per product, the set up cost per order, and the shortage cost per item and decision variables such as order quantity, safety factor, the number of shipments, and shipment increasing factor is figured out via sensitivity analysis. Finally, it is statistically proved that the mixed approach is superior to the existing approaches.

This paper is concerned with the single vendor single buyer integrated production inventory problem. To make this problem more practical, space restriction and lead time proportional to lot size are considered. Since the space for the inventory is limited in most practical inventory system, the space restriction for the inventory of a vendor and a buyer is considered. As product’s quantity to be manufactured by the vendor is increased, the lead time for the order is usually increased. Therefore, lead time for the product is proportional to the order quantity by the buyer. Demand is assumed to be stochastic and the continuous review inventory policy is used by the buyer. If the buyer places an order, then the vendor will start to manufacture products and the products will be transferred to the buyer with equal shipments many times. The mathematical formulation with space restriction for the inventory of a vendor and a buyer is suggested in this paper. This problem is constrained nonlinear integer programming problem. Order quantity, reorder points for the buyer, and the number of shipments are required to be determined. A Lagrangian relaxation approach, a popular solution method for constrained problem, is developed to find lower bound of this problem. Since a Lagrangian relaxation approach cannot guarantee the feasible solution, the solution method based on the Lagrangian relaxation approach is proposed to provide with a good feasible solution. Total costs by the proposed method are pretty close to those by the Lagrangian relaxation approach. Sensitivity analysis for space restriction for the vendor and the buyer is done to figure out the relationships between parameters.

As order quantity is increased, the ordering cost per item will be cheaper due to saving of transportation and material handling costs. In this paper, two realistic assumptions such as quantity discount and budget limit are considered. Quantity discount means that all units in the order will be discounted according to the predetermined order levels. Budget limit represents that the costs for inventory investments are bounded. This paper develops a Lagrangian relaxation approach for a continuous review inventory model with a budget constraint and quantity discounts. Computational results indicate that the proposed approach provides a good solution. Sensitivity analysis is done to get some insights on budget limit and quantity discount. As budget limit or the amount of discount according to order quantity is increased, order quantity is increased, whereas reorder point is not always increased.

The modular assembly system can make it possible for the variety of products to be assembled in a short lead time. In this system, necessary components are assembled to optional components tailor to customers’ orders. Budget for inventory investments composed of inventory and purchasing costs are practically limited and the purchasing cost is often paid when an order is arrived. Service cost is assumed to be proportional to service level and it is included in budget constraint. We develop a heuristic procedure to find a good solution for a continuous review inventory system of the modular assembly system with a budget constraint. A regression analysis using a quadratic function based on the exponential function is applied to the cumulative density function of a normal distribution. With the regression result, an efficient heuristics is proposed by using an approximation for some complex functions that are composed of exponential functions only. A simple problem is introduced to illustrate the proposed heuristics.

We develop an optimization algorithm for a periodic review inventory system under a stochastic budget constraint. While most conventional studies on the periodic review inventory system consider a simple budget limit in terms of the inventory investment being less than a fixed budget, this study adopts more realistic assumption in that purchasing costs are paid at the time an order is arrived. Therefore, probability is employed to express the budget constraint. That is, the probability of total inventory investment to be less than budget must be greater than a certain value assuming that purchasing costs are paid at the time an order is arrived. We express the budget constraint in terms of the Lagrange multiplier and suggest a numerical method to obtain optional values of the cycle time and the safety factor to the system. We also perform the sensitivity analysis in order to investigate the dependence of important quantities on the budget constraint. We find that, as the amount of budget increases, the cycle time and the average inventory level increase, whereas the Lagrange multiplier decreases. In addition, as budget increases, the safety factor increases and reaches to a certain level. In particular, we derive the condition for the maximum safety factor.

In this paper, we develop an efficient approach to solve a continuous review inventory system with a budget constraint when the semi-finished product and optional components are required to be assembled. We are, in particular, interested in a budget constraint that includes a service level. The service cost, such as labor and facility costs, tends to increase as the service level increase, and it makes the problem difficult to solve. Assuming that the reorder point for a semi-finished product is given, we show that the order quantity for the semi-finished product and the order quantity and reorder point for optional components can be determined by minimizing the total cost that includes setup cost, inventory holding cost, and shortage cost. The performance of the proposed approach is tested by numerical examples. By using sensitivity analysis, we conclude that, as the reorder point for semi-finished product increases, the order quantity for semi-finished product increases, whereas the order quantity and reorder point of optional components decreases.

If service level is increased, then service cost such as labor cost and facility cost will be increased. This service cost is included in the budget constraint in this paper. This service cost makes the problem difficult to solve. The purpose of this research is to develop an efficient approach for a continuous review inventory system with budget constraint when the semi-finished product and optional components are required to be assembled. Assuming that the reorder point for semi-finished product is given, order quantity for semi-finished product and order quantity and reorder point will be determined to minimize total cost that includes setup cost, inventory holding cost, and shortage cost. The performance of the proposed approach is checked by using an example.

This paper deals with a centralized warehouse problem with multi-item and capacity constraint. The objective of this paper is to decide the number and location of centralized warehouses and determineorder quantity (Q), reorder point (r) of each centralized warehouse to minimize holding, setup, penalty, and transportation costs. Each centralized warehouse uses continuous review in- ventory policy and its budget is limited. A SA (Simulated Annealing) approach is developed and its performance is tested by using some computational experiments.

Inventory centralization for a number of stores may reduce inventory costs by establishing and maintaining a central ordering and distribution point. In this study, a centralized warehouse problem with multi-item and capacity constraint is considered. The objective of this study is to develop a methodology to decide the number and location of centralized warehouses and determine order quantity(Q), reorder point(r) of each centralized warehouse to minimize holding, setup, penalty, and transportation costs. In this problem, each centralized warehouse uses continuous review inventory policy and its budget is limited. A SA(Simulated Annealing) approach for this problem is developed.

In this study, we propose a new method for generating candidate solutions based on both the Cauchy and the Gaussian probability distributions in order to use the merit of the solutions generated by these distributions. The Cauchy probability distribution