Digital transformation (DX) has a significant impact on the supply chain, and this could promote the utilization of data and digital technologies in all systems. In this study, a storage location assignment problem was investigated utilizing a DX method to improve the efficiency of picking operations in distribution centers by focusing on the schedules of stored items. Storage assignment policies utilizing the arrival and shipping information of items to determine the optimal or near-optimal storage allocations to shorten the travel distance were considered. First, it was assumed that all arrival and shipping dates of items in the planning horizon are known. Then, greedy policies focusing on arrival dates, shipping dates, and the storage durations of items were compared. The greedy policy based on shipping dates showed the highest performance. Next, the ways in which these properties can be utilized to obtain the optimal solution efficiently were investigated. Finally, under the assumption that information on the arrival and shipping dates of all items is incomplete, policies to improve the greedy policy using arrival dates were considered.

This paper considers an option contract in a two-stage two suppliers - one buyer supply chain (SC) when market demand is stochastic. The suppliers compete by offering a commitment option contract to the buyer. The con- tract is composed of three prices. It allows the buyer to purchase a firm quantity and reserve options before knowing the exact market demand. After realizing the exact demand, the buyer can choose the number of options to exercise. The aim of this paper is to determine an optimal ordering and selection strategy for the buyer. It also determines an optimal bidding strategy for the suppliers. Furthermore, this contract will be compared to a pure option contract. These contracts are justified through numerical examination, and it was found that buyers prefer the lower-cost products as as to satisfy the demand with a higher realization probability. Furthermore, it was found that in equilibrium, local suppliers earn profit from the exercised options, whereas overseas suppliers earn profit from the reserved options. The paper also shows that the commitment option price provides suppliers with a greater profit in comparison to a pure option contract under the same conditions.

In order to save individual virgin materials by recycling products, manufacturing companies must adopt new information technology to evaluate the environmental impact of their management. The transformative adoption of digital technology is referred to as digital transformation (DX), and the DX technique can be used to digitalize reverse supply chain management strategies for environmental issues. Before the use of the DX technique for a reverse supply chain, a decision maker (DM) was not be able to know the material types of the end-of-life (EOL) products based on their status until they had been recycled. However, using the DX technique, the DM is able to understand EOL product data such as the number and the amount of each material within the EOL products in advance. Therefore, the usage of the DX technique enables the DM to design the reverse supply chain network not only environmentally-friendly but also economical. In applying DX to supply chain networks, supply chain managers must cut costs and evaluate environmental impacts. In order to balance environmental and economic concerns, the DM can design a reverse supply chain network using a solving method for multi-criteria decision making such as linear physical programming (LPP). Using the LPP algorithm, the DM can calculate a harmonized weight for objective functions with a trade-off relationship. This study designs a reverse supply chain network for individual material recovery environmentally-friendly and economical by using LPP as one of the support methods in the era of DX. The academic contribution of this study is that the effect of objective functions for individual material types can be identified, and the practical contribution is that it enables us to find a reverse network solution based on individual materials being collected from EOL products recycled throughout numerical experiments with LPP.

It takes a large amount of experience and time to acquire welding skills, especially since documenting such skills is difficult. There is a correlation between the body movements of a welder and the welding quality; this link should be proved for transferring welding skills from skilled welder to inexperienced welders. We have experimented with shielded metal arc welding at an actual business establishment to measure a welder's body motions. This was achieved by focusing on the welder's head and arm movements as well as the welder's angles of axial rotations. In this study, a non-contact, three-dimensional shape-measuring device was used to measure and analyze the surface shapes of welded materials, particularly the shapes of beads, for the purpose of associ ating welding quality with body motions as a basic study for future research. Individual welding skill was considered when determining the level of quality, and the quality level was based on the differences in the surface shapes of the welded materials and how they correlated with the welders' varying years of experience. Therefore, this study proposes analyzing the surface profiles of completed shielded metal arc welds by various workers to obtain a discriminant that distinguishes their degrees of experience.

Today, manufacturing companies are increasingly interested in digital transformation (DX). One reason for this is the high number of big and successful companies worldwide that have already become digital natives. However, companies that own several existing businesses are having difficulties in adopting this new way of organizing their trades via DX. Considering these issues, this study aims to take the first step to understand the process of DX applied to quality function deployment (QFD), and how companies can implement this transformation in their businesses.

As the vertically integrated supply chain structure converts into a horizontal division of labor, manufacturers of modular consumer electronics, such as liquid-crystal display televisions, personal computers, and smartphones, find it difficult to achieve adequate profits by selling products to retailers with contract terms decided through negotiation. The double marginalization phenomenon caused by information asymmetry, market power deviation, and self-interest consideration in such negotiations has been discussed in many previous studies. With double marginalization, the total profit of both negotiation participants is much lower than the monopoly profit in the supply chain. This study considers a two-level supply chain consisting of a liquid-crystal display television manufacturer and a mass retailer. A new trading system is proposed to improve the profit of the manufacturer by improving the total profit of the supply chain. With realistic data estimated by the financial statements of Japanese manufacturers and retailers, the effectiveness and applicability of the proposed trading system is confirmed through numerical experiments.

Stable operation of the systems existing in modern society is crucial. The component assignment problem (CAP) is important for improving the reliability of a system through efficient use of the components. The CAP involves the seeking of an arrangement that maximizes the system reliability given the components included in the system. To solve this problem, we use a model that represents a real system as a system model, such as the connected-X-out-of-(m, n):F system. The optimal arrangement for a connected-(r, s)-out-of-(m, n):F system, which is a type of connected-X-out-of-(m, n):F system, has been previously investigated. However, linear connected-(1,2)-or-(2,1)-out-of-(m, n):F systems have not been studied because the necessary conditions cannot be proved using conventional methods. Therefore, in this study, we focus on a linear connected-(1,2)-or-(2,1)-out-of-(2, n):F system and propose an efficient search method for the optimal arrangement. To efficiently seek the optimal arrangement of this system, we propose alternating arrangements as the necessary condition for optimal arrangement along with an algorithm that applies this condition. We propose and prove lemmas necessary for proving the theorem. In addition, we compare the proposed algorithm with an enumeration algorithm and an algorithm that does not exclude nonalternating arrangements and confirm its effectiveness.

In many universities, the schedule for assigning classrooms to classes is often performed manually by staff. With the constraints such as classroom equipment, classroom capacity, number of students taking the classes, and requirements of professors and students for the classes, manually solving the classroom assignment problem is a complex and time-consuming task. Therefore, we present a classroom assignment support system that solves the problem using a network flow model. The proposed system can be used to provide an assignment that satisfies the conditions and requirements in a short time and reduces the workload of the staff.

In this paper, the authors adopt a multi-dimensional approach for visibility evaluation comprised of a series of experiments where multiple human data (conventional subjective ratings on visibility and eye-tracking data) and interpretation schemes are utilized to elicit visibility-related aspects from data. In this approach, an effective combination of multiple data to analyze the visibility of platform displays was proposed considering managerial limitations (e.g., time, cost, skill/knowledge needed for implementation). The proposed approach was applied to an experiment where comparative visibility evaluations between three platform displays were carried out. The results of each dimension of visibility evaluations and the feasibility of practical implementation of the approach are discussed.