Kwangyeol Ryu

Agent-based fractal architecture and modelling for developing distributed manufacturing systems

For their timely response to the rapidly changing manufacturing environment and markets, future manufacturing systems must be flexible, adaptable, and reusable. Recently, bionic (or biological), holonic, and fractal manufacturing systems (FrMS) have been discussed as potential candidates for the next generation of manufacturing systems. This study focuses on the FrMS, which is based on the concept of autonomous cooperating agents referred to as fractals. The major component of the FrMS is a basic fractal unit (BFU). It consists of five functional modules: observing module (observer), analysing module (analyser), resolving and executing module (resolver), organizing module (organizer), and reporting module (reporter). Although the FrMS has many conceptual advantages, the implementation of the system has been known to be difficult. This paper is a preliminary study of the basic components and the architecture with an eye toward the future implementation of FrMS. In order to describe the characteristics of a fractal, this paper presents several models including function models using IDEF0, working models using Petri-net, and static/dynamic models using the unified modelling language (UML).

Conflict detection and resolution for goal formation in the fractal manufacturing system

The fractal manufacturing system (FrMS) is based on the concept of autonomously cooperating agents referred to as fractals. A fractal is a set of self-similar agents whose goal can be achieved through cooperation, coordination, and negotiation among the agents for themselves. A fractal has fractal-specific characteristics (e.g. self-similarity, self-organization, self-optimization, goal-orientation, and dynamics), and it also has the characteristics of an agent (e.g. autonomy, mobility, intelligence, cooperation, and adaptability) at the same time. In the FrMS, a goal can be regarded as the status which the system aspires to be in. The goal-formation process (GFP) in the FrMS is a process of generating goals and modifying them by coordination between agents. In the GFP, conflicts may occur between goals, which can drive a system to become inefficient. In this paper, a conflict resolution mechanism via agent-based negotiation is proposed for facilitating the GFP. The scheme deals with non-fixed goals. The mobile agent-based negotiation process (MANPro), in which a mobile agent is used for information-exchanging and problem-solving, is used for negotiations in this scheme. The proposed mechanism is illustrated with a goal formation scenario in an exemplary FrMS.

Goal-orientation mechanism in a fractal manufacturing system

Decomposition of tasks in ordinary manufacturing systems is usually based on the predefined goal of the system. To achieve the high-level goals (e.g. factory goal or company goal), several subgoals should be achieved in advance. However, goals can dynamically change along with the current status of the system and the external environmental situations. Thus, a manufacturing system should support the goal formations, which can bear these changes for efficient and effective operations. Therefore, it is necessary to develop a systematic methodology for goal formations in a manufacturing system. In particular, the formation and/or change of goals in real-time should be possible for distributed and dynamic systems including a fractal manufacturing system (FrMS). However, most researchers have started their study from an assumption that every goal in the system is naturally well defined. This paper proposes a methodology for the goal-formation process (GFP), which embodies one of the characteristics of a fractal (i.e. goal orientation) in the FrMS. In order to generate fuzzy goals and propagate them in the system, fuzzification/defuzzification and goal-generation procedures are presented in detail. For easy understanding of the procedure, an exemplary goal generation is also illustrated within the proposed GFP framework. By applying the GFP, we expect that the manufacturing system would become autonomous and flexible by generating and evolving goals without human intervention.

Supply chain coordination under budget constraints

We study supply chain coordination under budget constraints.We develop a revenue-sharing-and-buy-back (RSBB) contract.The RSBB contract can achieve supply chain coordination under budget constraints.The RSBB contract is more flexible than the revenue-sharing and buy-back contracts. Budget constraints are commonly considered in real decision frameworks; however, the literature has rarely addressed the design of contracts for supply chains with budget-constrained members and in which capital costs are considered. In this article, we study supply chain coordination of budget-constrained members when a financial market is unavailable. We propose a revenue-sharing-and-buy-back (RSBB) contract that combines revenue-sharing (RS) and buy-back (BB) contracts. We compare the performance of RS, BB, and RSBB contracts under a coordinated two-stage supply chain in which members experience budget constraints. Results show that the RS and BB contracts are not feasible under certain budget scenarios, whereas the RSBB contract can always be used to coordinate the supply chain and arbitrarily divide profits. We propose a profit allocation approach to address information symmetry created by undisclosed budget thresholds. Our analytical and numerical results provide insight into how managers select an appropriate contract based on their budget scenarios and capital costs.

Self-reconfigurable software architecture: Design and implementation

To respond quickly to the rapidly changing manufacturing environment, it is imperative for the system to have such capabilities as flexibility, adaptability, and reusability. The fractal manufacturing system (FrMS) is a new manufacturing paradigm designed to meet these requirements. To facilitate a dynamic reconfiguration of system elements (i.e., fractals), agents as well as software modules should be self-reconfigurable. Embodiment of a self-reconfigurable manufacturing system can be achieved by using self-reconfigurable software architecture. In this paper, therefore, self-reconfigurable software architecture is designed by conducting the following studies: (1) analysis of functional requirements of a fractal and environmental constraints, (2) design of reconfigurable software architecture especially for a reconfigurable agent, (3) selection of proper techniques to implement software modules, and realization of software architecture equipped with self-reconfigurability. To validate this approach, the designed architecture is applied to the FrMS.

Reinforcement learning approach to goal-regulation in a self-evolutionary manufacturing system

Highlights? We propose a goal-regulation mechanism that applies a reinforcement learning approach to autonomous goal-formation. ? Individual goals are regulated by a neural network-based fuzzy inference system called goal-regulation network (GRN). ? The GRN is updated by a reinforcement signal from another neural network called goal-evaluation network (GEN). ? The GEN approximates the compatibility of goals with current environmental situation. ? The proposed mechanism is validated by a simulation study on a production planning problem. Up-to-date market dynamics has been forcing manufacturing systems to adapt quickly and continuously to the ever-changing environment. Self-evolution of manufacturing systems means a continuous process of adapting to the environment on the basis of autonomous goal-formation and goal-oriented dynamic organization. This paper proposes a goal-regulation mechanism that applies a reinforcement learning approach, which is a principal working mechanism for autonomous goal-formation. Individual goals are regulated by a neural network-based fuzzy inference system, namely, a goal-regulation network (GRN) updated by a reinforcement signal from another neural network called goal-evaluation network (GEN). The GEN approximates the compatibility of goals with current environmental situation. In this paper, a production planning problem is also examined by a simulation study in order to validate the proposed goal regulation mechanism.

Channel coordination for multi-stage supply chains with revenue-sharing contracts under budget constraints

Real-life situations show that revenue-sharing (RS) contracts used in multi-stage supply chains have more complex structures than those that have been studied in recent research. In this paper, we study RS contracts in multi-stage supply chains where some members work with more than one upstream member. This general supply chain structure closely resembles those in actual practice under RS contracts. The literature on supply chain contracts has not adequately addressed contract design for supply chains with members who face budget constraints. We show that the RS contract could fail to coordinate supply chains when members are under particular budget constraints. In response, we propose a revenue-sharing with budget constraints (RSB) contract that adds no administrative cost. A properly designed RSB contract can be used to achieve supply chain coordination and to arbitrarily allocate profits in multi-stage supply chains. Our numerical results provide insights into ways supply chain coordination can be achieved under budget constraints through the RSB contract.

Framework for fractal-based supply chain management of e-Biz companies

The high degree of uncertainty of customer demand makes it difficult for e-Biz companies to facilitate their profit maximization. The type of e-Biz company focused in this paper is a B2C (business-to-customer) which connects customers with product manufacturers through the Web interface. In this paper, the B2C company interacts with customers, multiple external manufacturers and a single transportation system. To deal with complicated interactions and relationships among customers, manufacturers and a transportation system, a comprehensive management system to support the B2C company is inevitable. This paper proposes a fractal-based framework for the management of e-Biz companies, where each member in the supply chain is modelled with a self-similar structure referred to as a ‘fractal’. The basic fractal unit (BFU) consists of five functional modules, including an observer, an analyser, a resolver, an organizer and a reporter. In this paper, functions of each module will be defined with UML (Unified Modelling Language). Then, the analysers and the resolvers (modules associated with decision-making) for each individual fractal will be specified with mathematical models. A profit model for the company-level fractal will then be formulated. Finally, a numerical example for an exemplary e-Biz company functioning B2C will be presented for the illustration of the proposed methodology.

Reconfiguration framework of a supply network based on flexibility strategies

Because the supply network of an enterprise should be flexible enough to capture and overcome market dynamics, one of the major concerns of global enterprises is to make their supply network reconfigurable. Although many strategies for flexible management of a supply network have been proposed, especially for mitigating supply network risks, it still remains unclear how to apply the strategies to a supply network and how to reconfigure the supply network. This paper examines the influence of flexibility strategies in a dynamic global market environment on the structure of supply network, and proposes a method of reconfiguring the supply network of an enterprise to cope with its flexibility strategies. A reconfigurable supply network model is proposed, and flexibility strategies are classified, and critical indices of strategies are defined. In the proposed model, each business actor is defined as a network node and each node has its own goal. A node optimizes its goal to reduce and overcome the risk of market environments. The result of optimization indicates that the supply network structure is reconfigured dynamically.

Labour productivity in modular assembly: a study of automotive module suppliers

Modular assembly is being applied to an increasing number of vehicles and part manufacturers to manage the ever-changing demands of the automotive industry. In spite of many researches performed on the supply chain management and logistics aspects of modular production, there is no research discussing modular production line concepts used by module suppliers. In this paper, labour productivity of two assembly line concepts including the conveyor line and box assembly line is studied under modular production environment. Both line concepts and respective assembly processes are described in detail. Mathematical models showing the total work faced by these two assembly line concepts are developed and compared. Two productivity scales are defined: the maximum achievable productivity and the actual productivity. The labour productivity rates of these assembly line concepts on above productivity scales obtained from calculations and a simulation are compared as a performance measure.