A commercial custom called ゛One-Third Rule″ is suspected to increase the amount of Food loss in Japan. The rule being unique to Japan sets deadlines for delivery to retailers and sales to customers. It is likely that the shorter the time from production to expiration, the higher the impact of the rule. Thus, this study focuses on the milk supply chain and simulates how milk products are transferred across a supplier, a retailer, and consumers. As a first step to mitigate the problem of Food loss, this study unravels a relationship between the deadlines and the
amount of Food loss.
Unexpected interruptions in manufacturing such as machine breakdowns incurs degradation of productivity.This study aims to build an automatic scheduling method that can respond to the occurrence of uncertain events flawing a schedule and catch up with the planned schedule as quickly as possible. We here focus on building an adaptive operation planning of a material handling robot according to the predetermined schedule revision policy to cope with uncertainties and to reduce the total downtime of the manufacturing system. The applicability of the proposed method is demonstrated through physical experiments.
In Japan, aging of the population is accelerating year by year, and the number of people requiring care is also increasing. Demand for nursing care services is expected to increase further in the future. The demand for day-care facilities where provide care services to ambulatory users is particularly high. In the day-care facilities, it is necessary to pick up and drop off the user by car. Therefore, vehicle routing and sheet assignments should be determined considering not only the efficiency of transfer but also the physical and psychological conditions of the users. In this study, we propose a coevolutionary genetic algorithm-based method to determine the seat assignment for cars and the traveling route of users.
Recently, almost all the quality inspection work in the manufacturing industry is automated. However, there are many products for which inspection work cannot be automated. Since the tip of a rotating tool (Diamond bar) for dental care is attached with diamond particles, all parts are slightly different. In this study, we will develop a tool to replace manual inspection. As basic research, we constructed a parts model using neural network and convolutional neural network. The model was evaluated under various conditions.
We developed a standard function such as shape recognition function, feature quantity measurement function and other function necessary for design rule check, and developed design rules related to manufacturability based on a technology that digitally express design rules by combining these standard functions. As an example, we explain two design rules implemented by combining these standard functions, design rules to be checked during injection molding and casting.
High-speed and high-precision machine tools developed recently have contributed to shorten machining time in parts machining. However,process planning still depends on skillful experts to determine manufacturing information such as machining sequence, cutting tool and so on. As a result, the increase in the ratio of preparation time is an issue for realizing high-mix low-volume production. Therefore, it is expected to improve the efficiency of parts machining by achieving the automation of process planning. In this study, case-based reasoning based on recognized machining features is adopted to determine manufacturing information in parts machining.
Since process planning requires skilled techniques and a lot of labor, the automated process planning is the ultimate goal to achieve highly efficient machining. On the other hand, the results of process planning for similar target shapes are almost same each other. If past machining cases are effectively used by linking the target shape to manufacturing information such as machining sequence and cutting conditions, the automated process planning would be realized and machining know-how of skillful experts could be also introduced. Therefore, a system is developed to detect past similar target shapes and the manufacturing information based on CAD model of the target shape in this study. A case study is conducted to confirm the usefulness of the developed similar shape detection system.
Today, much of the manufacturing industry is on the verge of producing a high variety of products with lower costs and shorter delivery times, in response to growing competition. This development can be advanced by promoting quick changeover practices such that companies can achieve lean and flexible manufacturing capability. To his end, an established door hardware firm in Melaka, Malaysia has applied Single Minutes Exchange of Die (SMED) so as to shorten changeover times in the operation of its Pressure Die Casting machine. The goals of this review are to examine the firm’s on-going changeover processes, to propose newer operational procedures for these changeover processes, followed by validation of the new procedures. This review only focused on the firm’s Pressure Die Casting 1 machine. The root causes were determined by performing time studies, video recordings, direct observation, and interview sessions. By implementing SMED, wastage in changeover processes could be reduced. Existing changeover procedures were analysed, while internal and external tasks were recognised and separated through the use of checklists, performing-function checks, and transport of mould improvements. The conversion of internal tasks to external tasks was accomplished through implementation of the ECRS and 5S approaches. Every aspect of the changeover processes was streamlined with regards to parallel operations among setters and operators, usage of the functional clamp, and improvements in fixture and hose line connections. Consequently, newer operating procedures were developed and applied for easier and faster operation. Validation of these newer procedures established a changeover time reduction of some 201 minutes down to 107 minutes, or 94 minutes in all, which equates to a 46.77% reduction in changeover time. Clearly, this review showed that SMED comprised one of the more powerful LM techniques for optimising process changeover.
Recently, crowdsourced manufacturing concept highly attracts attention. In crowdsourced manufacturing, each company shares its manufacturing resources to improve asset efficiency. To design such systems, it is important how to (1) make matching between resource requests and offers to achieve high profit for whole system and (2) give incentives for participants to make them act in a fair way, i.e. make matching methods 'strategyproof'. In this paper, we propose a new resource matching method based on 'nucleolus' concept in cooperative
game theory. The computational results show the proposed method balances high efficiency and better strategyproofness.