Toshiya Kaihara

Multi-Agent based Supply Chain Modelling with Dynamic Environment

Supply chain management (SCM) is not always concerned with optimal solutions conventionally in terms of product allocation. Virtual market based supply chain operation solves the product allocation problem by distributing the scheduled resources based on the agent interactions in the market. We formulate supply chain model as a discrete resource allocation problem under dynamic environment, and demonstrate the applicability of the virtual market concept to this framework. The proposed algorithm facilitates sophisticated SCM under dynamic conditions. r 2003 Elsevier B.V. All rights reserved.

Supply chain management with market economics

Abstract Supply chain management (SCM) is now recognised as one of the best means by which enterprises can make instant improvements to their business strategies and operations. SCM, however, is generally based on the simple theory of constraints (TOC) concept, and is not always concerned with Pareto optimal solutions in product distribution. Since market price systems constitute a well-understood class of mechanisms that under certain conditions provide effective decentralisation of decision making with minimal communication overhead, we propose SCM based on market-oriented programming in this paper. In market-oriented programming, we take a metaphor of economy computing multi-agent behaviour literally, and directly implement the distributed computation as a market price system. We define the agent activities to negotiate the tradeoffs of acquiring different resources, so as to realise the multi-echelon optimisation. Several simulation experiments on the supply chain model with multi-echelon structure clarify the market dynamics that emerge through the agent negotiations. It is confirmed that careful constructions of the decision process according to economic principles can lead to Pareto optimal resource allocations in SCM, and the behaviour of the system can be analysed in economic terms.

A distributed virtual factory in agile manufacturing environment

There is a growing recognition that current manufacturing enterprises must be agile, that is, capable of operating profitably in a competitive environment of continuously changing customer demands. The use of a virtual enterprise (VE) is becoming increasingly prevalent, and that has been made possible, in part, due to the significant advances in communication and information technology in recent years. A manufacturing system is one of the competitive factors that forms an effective VE. Therefore, for manufacturers wishing to obtain a contract in VE, it is crucial to present attractive and competitive offers to other coalition members. There are several criteria to these offers, such as cycle time, fulfilment of due date or quick shipping date, cost, and quality assurance for the ordered products. Manufacturing system simulation could endorse the basic estimates of the criteria for the strategic offer. The distributed simulation model concept provides practical solutions to facilitate such a large-scaled precise simulation model in the VE environment, because it is constructed as the integration of several manufacturing simulation models of each production module in the factory. As a solution to realize this integration, we propose a Distributed Virtual Factory (DVF) concept that consists of distributed precise simulation models connected by several synchronization mechanisms named Time Bucket algorithms. A DVF enables precise evaluations of the whole manufacturing system, especially in terms of the material flows. In this study, we introduce an Activity Based Costing (ABC) method into the DVF architecture to estimate the detailed cost analysis of the products. The methodology facilitates strategic enterprise management to prepare the request for the bids in the VE environment. The effectiveness of the proposed concept in agile manufacturing is discussed with simulation experiments.

Synchronization Mechanisms for Integration of Distributed Manufacturing Simulation Systems

In this paper, a virtual factory is proposed in the form of a distributed simulation model which provides a tool for performance evaluation of large and complex manufacturing systems. The virtual factory is constructed on a computer net work developed for computer-integrated manu facturing (CIM). The relationship between the structure of a distributed simulation system and the model of a manufacturing system is de scribed, and then basic requirements for the vir tual factory are prescnted. Several Time Bucket methods, called Single-Phased Bucket, Double- Phased Bucket and Modified Double-Phased Bucket, are proposed as a synchronization mechanism to construct a distributed manufac turing simulation system, and their characteris tics and effectiveness are discussed from the viewpoint of modeling a manufacturing system.

Cloud-Based Automated Design and Additive Manufacturing: A Usage Data-Enabled Paradigm Shift

Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usage information is not available on a large scale and (b) product optimization requires considerable efforts in terms of manpower and adaptation of production equipment. However, with the advent of cloud-based services and highly flexible additive manufacturing techniques, these obstacles are currently crumbling away at rapid pace. The present study explores the state of the art in gathering and evaluating product usage and life cycle data, additive manufacturing and sensor integration, automated design and cloud-based services in manufacturing. By joining and extrapolating development trends in these areas, it delimits the foundations of a manufacturing concept that will allow continuous and economically viable product optimization on a general, user group or individual user level. This projection is checked against three different application scenarios, each of which stresses different aspects of the underlying holistic concept. The following discussion identifies critical issues and research needs by adopting the relevant stakeholder perspectives.

Supply Chain Management Based on Market Mechanism in Virtual Enterprise

Supply chain management is not always concerned with the optimal solutions in terms of product distribution. Market mechanism solves product distribution problem by allocating the scheduled resources according to market prices. We formulate supply chain model as a discrete resource allocation problem, and demonstrate the applicability of economic analysis to this framework. The proposed algorithm facilitates sophisticated supply chain management, which conducts a pareto optimal solution in product distribution system.

Game theoretic enterprise management in industrial collaborative networks with multi-agent systems

Nowadays, virtual enterprise (VE) is an important paradigm of business management in an agile environment. VE exists in several kinds of business organization through multi-layered product flows. It is obvious that a mechanism, through which these different enterprises can be integrated together, is required for the better management of VE. In this paper, we focus on the negotiation process in VE formulation as a basic research to clarify its effective management. Each enterprise in VE is defined as a software agent with multi-utilities, and three types of primitive business models are targeted, such as the vertically integrated business model, horizontally specialized business model and hybrid business model. We develop a three-layered VE model for computer simulation so as to clarify VE formulation dynamism with the proposed negotiation mechanism.

Method for Target Tracking in Focused Ultrasound Surgery of Liver using Magnetic Resonance Filtered Venography

The purpose of this work is to develop a magnetic resonance (MR) technique for guiding a focal point created in focused ultrasound surgery (FUS) onto a specific target position in an abdominal organ, such as the liver, which moves and deforms with respiratory motion. The translational distance, rotational angles, and amount of expansion and contraction of the organ tissue were measured by obtaining the gravity points of the veins filtered from the sagittal, cine MR images of healthy livers during free breathing. Using the locations of the vessels at each time point, the target position at which the ultrasound focus was to be placed was estimated. In the volunteer experiments (N = 2), the lower limit of the spatial matrix dimension for delineating the veins was 128 x 128. The average displacement of the liver was 19.6 + 3.6 mm in superior-inferior (SI) direction and 3.1 + 1.4 mm in anterior-posterior (AP) direction. The deformations were 3.7 + 1.1 mm in SI direction and 3.0 + 1.2 mm in AP direction. The error between the actual and the estimated target point was 0.7 plusmn 0.5 mm in SI direction, 0.6 plusmn 0.4 mm in AP direction and 1.0 plusmn 0.5 mm in distance, and less than 2.1 mm in all the trials. These results suggested that the proposed technique is sufficient for targeting the focus on a specific tissue location and for tracking the slice slab for thermometry to cover the region of focus.

Virtual Enterprise Coalition Strategy with Game Theoretic Multi-Agent Paradigm

Nowadays, Virtual Enterprise (VE) is a crucial paradigm of business management in agile environment. VE exists in several kinds of organizations, although the complexity of the each enterprise in VE may vary greatly. Clearly, there is a need for a mechanism through which these different enterprises can be integrated together. In this paper, we focus on negotiation process in VE formulation as a basic research to clarify its effective management. Each enterprise in VE is defined as software agent with multi-utilities and a framework of multi-agent programming with game theoretic approach is proposed as negotiation algorithm amongst the agents. We develop a computer simulation model to form VE through multiple negotiations amongst several potential partners, and finally clarify the formulation dynamism with the proposed negotiation process.

Optimization and Simulation of Collaborative Networks for Sustainable Production and Transportation

Complex and delocalized manufacturing industries require high levels of integration between production and transportation in order to effectively implement lean and agile operations. There are, however, limitations in research and applications simultaneously embodying further sustainability dimensions. This paper presents a methodological framework based on optimization and simulation to integrate aggregate optimized plans for production and multimodal transportation with detailed dynamic distribution plans affected by demand uncertainty. The objective function of the optimization model considers supply, production, transportation, and CO2 emission costs, as well as collaboration over the multimodal network. Bill-of-materials and capacity constraints are included. A feedback between simulation and optimization is used to plan requirements for materials and components. Computational experiments are based on realistic instances. Results demonstrate that the framework can be effectively used to analyze cost-CO2 emission tradeoffs, effects of demand uncertainty, and collaborative distribution strategies on economic and environmental performance of the supply chain.