Fractal Manufacturing System Research Articles

Development of the Architecture and Reconfiguration Methods for the Smart, Self-Reconfigurable Manufacturing System

Over recent decades, the demand for smarter and more intelligent manufacturing systems has increased in order to meet the growing requirements of customers. Manufacturing systems are termed as smart manufacturing systems (SMSs); these systems are capable of fully integrated autonomous operation. Specifically, the concept of autonomous systems and functions has been adopted for next generation manufacturing systems (NGMSs). Among these NGMSs, the fractal manufacturing system (FrMS) exhibits several characteristics that are similar to those of SMSs. Therefore, in this paper, a smart, self-reconfigurable manufacturing system (SSrMS) based on the FrMS is proposed. The proposed SSrMS architecture was designed for realizing self-reconfiguration functions based on the FrMS concept. SSrMS exhibits a fractal structure, which enables the distribution of control features; this also constitutes the fundamental basis of autonomous operation and reconfiguration between each fractal. SSrMS architecture includes the use of big data, digital facilities, and simulations. Furthermore, we introduce three reconfiguration methods to conduct system reconfiguration, which are a goal decision model, a negotiation model, and a sustainability assessment method. The goal decision model was developed to determine a goal of each fractal to achieve the system’s goal. In other words, each fractal can decide a goal to achieve the system’s goal, such as maximizing productivity or profit, or minimizing cost, and others. The negotiation model was adopted to perform partial process optimization by reassigning tasks and resources between the fractals, based on the goal of coping with the changes in the system’s condition. The sustainability assessment method was designed to simultaneously evaluate sustainability with respect to the system’s goals. The proposed architecture of SSrMS with goal decision model, negotiation model, and sustainability assessment method has the features of self-optimization, self-organization, and self-reconfiguration in order to achieve fully autonomous operations for the manufacturing system. The proposed architecture including three methods are expected to provide a fundamental study of the autonomous operations. The main findings of in this study is the development of a new architecture for fully autonomous operations of the smart manufacturing system with reconfiguration methods of goal-oriented manufacturing processes.

자가재구성 가능 생산시스템을 위한 목적모델 개발

A fractal manufacturing system (FrMS) is one of the most advanced and self-reconfigurable manufacturing systems among the available manufacturing systems, which is based on the concept of autonomously cooperating agents referred to as fractals. In order to determine and generate goals or objectives, the FrMS use goal-orientation mechanism which includes goal-formation process (GFP). Generating goals as well as sub-goals requires a model defined from mutual relationships or networks among various objectives such as productivity, quality, and etc. However, previous research studies have not yet defined such discussion regarding mutual relationships among goals or sub-goals. The goal model is crucial in order to change the final goal in the manufacturing system. Therefore, this paper, proposes the development of a goal model for the FrMS by analyzing former objectives/goals while obtaining a new goal from manufacturing datasets. The result of goal model for FrMS is not permanent, but it is adjustable based on the changing environment. If the final goal changes, then lower-level goals will also change to help achieving the new final goal. The proposed mechanism for the goal model is developed to complete and support the goal-orientation technology by adjusting company’s goal. The proposed goal model provides a basis for flexibly changing system’s goal in the manufacturing system and proposed model enables faster response to cope with changing goal by system’s requirement.

Development of Goal Model Mechanism for Self-reconfigurable Manufacturing Systems in the Mold Industry

In Fractal Manufacturing System (FrMS), goal-orientation is solved by its distinguished technology, which is the goal-formation process (GFP). GFP consists of three procedures, which are goal-generation process (GGP), goal-harmonizing process (GHP), and goal-balancing process (GBP). However, in order to operate the goal-orientation technology, it requires the development of the defined goal model mechanism which can show the relationship between goals. FrMS requires a development of goal model in order to define mutual relationships between multiple objectives or goals such as performance, productivity, quality, flexibility, and so on. Therefore, this paper proposes the development of goal model for FrMS by analyzing former objectives or goals and obtain a new goal based on manufacturing dataset from mold industry. In order to develop the FrMS goal model, hierarchy in the reference goal model is identified and logics is developed for creation of bottom-leveled tasks in the reference model. After analyzing how their mutual relationships could affect the generation of goals and sub-goals, the initial goal model can be established and customized subjectively regarding to each company or factory’s preference. In order to establish initial goal model, support vector machine is used. The proposed goal model mechanism is developed to complete and support the goal-orientation technology by adjusting company’s goal.

The Holonic View of Organizations and Firms

In the world of organizations, firms, management and control, in general, a silent conceptual movement has been under way for less than 50 years now, beginning in 1967, when Arthur Koestler formally introduced the concepts of holon, holarchy (a hierarchical structure of holons) and holonic network (a reticular structure of holons). Thirty years later, Ken Wilber tried to generalize the holonic perspective. The new holonic perspective forces us to observe the surrounding universe (at a physical and biological level, and in the real or formal sense) by taking into account the whole/part (holarchies) and the before/after (holonic networks) relationships: any observable unit is at the same time a whole—composed of smaller parts—and part of a larger whole. In order to clarify the holonic vison and the ideas behind holons, holarchies and holonic networks, this study will examine some significant uses of these concepts and, in particular, the main sources of inspiration for those production systems referred to as the holonic manufacturing systems, comparing these to those defined as bionic and fractal manufacturing systems. Some forms of inter‐organizational networks, as well as holonic and virtual organizations, have also been considered. Copyright © 2017 John Wiley & Sons, Ltd.

Evaluation of cellular manufacturing configurations in dynamic conditions using simulation

This paper investigates the performance of classical cellular manufacturing systems compared to other two systems proposed in literature: fractal cells and remainder cells. This paper proposes three strategies to control a cellular manufacturing system with remainder cell and how to configure and control a fractal manufacturing system. The performance measures of the manufacturing systems are analyzed when several unforeseen events occur as: machine breakdowns, production mix changes, demand fluctuations, and processing time variability. A simulation environment developed by Arena® package was used to investigate the three manufacturing system configurations. The performance measures investigated are: throughput, throughput times of the parts, work in process, manufacturing utilization, and due date performance (tardiness). The simulation results show how the fractal and remainder cells can be a valid alternative to cellular manufacturing systems in a very dynamic environment.

Goal-balancing process for goal formation in the fractal manufacturing system

The coordination architecture and mechanisms are proposed for the goal-balancing process (GBP), which is one of the components of goal-formation process (GFP) in the fractal manufacturing system (FrMS). Since each agent in the FrMS generates, achieves and modifies its own goal autonomously during the coordination process with other agents, it is necessary to develop a systematic methodology for the goal-formations in a manufacturing system: GFP takes charge of this methodology, which enables the formation of and the changes in goal through coordination between agents in real-time in the distributed and dynamic systems. The GFP is composed of three sub-processes: the goal-generating process (GGP), the goal-harmonizing process (GHP), and the GBP. The GGP makes and propagates goals for all fractals. The GHP then eliminates or reduces possible conflicts and interferences between goals generated in GGP. The GBP is the post-process of GHP; it refines the fractal's goal, which has been ridded of conflict during the GHP to enhance the global performance of the system, rather than maximizing the performance of each fractal. For the development of the GBP we proposed a mechanism for unit goal-balancing process (UGBP), which is the basic process of GBP that adopts the, fuzzy decision-making, and distributed problem solving approaches.

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.

Dynamic restructuring process for self-reconfiguration in the fractal manufacturing system

To meet the rapidly changing customer needs in the manufacturing environment, future manufacturing systems must be dynamically and flexibly reconfigured. The fractal manufacturing system (FrMS) is one of the new manufacturing paradigms that can meet such requirements. The basic component of the FrMS is referred to as a fractal. Consisting of self-similar agents, each fractal autonomously cooperates and negotiates with others to coordinate its tasks. Dynamic restructuring process (DRP) supports reorganization of the system configurations so that the FrMS can be adapted to dynamically changing environments. Although traditional approaches have endeavoured to demonstrate reconfigurability of a manufacturing system, they are not accurate enough to meet the requirements of circumstances such as high-level autonomy in reconfiguring the system architecture. In this paper, therefore, the DRP, which embodies self-reconfigurability of a system, is proposed focusing on the FrMS. To check the effectiveness of the DRP, we have developed the FrMS test bed and conducted the experimentation on the DRP. A simulation study has been conducted to show the effectiveness of the DRP under an illustrative situation.

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.

An integrated approach for shop floor configuration in fractal manufacturing systems

Fractal manufacturing is an emerging concept that allocates the production resources into similar multifunctional cells capable of processing a wide variety of products. In this paper, an integrated methodology for shop floor configuration in fractal manufacturing systems is proposed. The procedure incorporates the different fractal cell design phases and methods that respond to varying organisational objectives. Mathematical models for the different design stages are presented and the validity of the procedure used for product allocation optimisation is evaluated. The quality of the resulting fractal layouts is assessed and compared against values for a typical random machine arrangement to evaluate the effectiveness of the product flow optimisation process. The results indicate that the procedure is efficient and that cell layout optimisation can improve material handling distances.

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.

Pattern Based Analysis of Fractal Manufacturing systems

Self-organization, self-optimization, and goal orientation in fractal manufacturing systems requires special treatment when solving planning or decision making tasks in highly dynamic environment. In this paper the parametric model checking technique is proposed as possible candidate for fractal analysis. As a main contribution, a flexible modeling technique is presented that bases on model patterns and pattern transformations.

Modeling and specifications of dynamic agents in fractal manufacturing systems

In order to respond to a rapidly changing manufacturing environment and market, manufacturing systems must be flexible, adaptable, and reusable. The fractal manufacturing system (FrMS) is one of the new manufacturing paradigms that address the need for these characteristics. The FrMS is comprised of a number of “basic components”, each of which consists of five functional modules: (1) an observer, (2) an analyzer, (3) an organizer, (4) a resolver, and (5) a reporter. Each of these modules, using agent technology, autonomously cooperates and negotiates with others while processing its own jobs. The resulting architecture has a high degree of self-similarity, one of the main characteristics of a fractal. Despite the many conceptual advantages of the FrMS, it has not been successfully elaborated and implemented to date because of the difficulties involved in doing so. In this paper, the static functions and dynamic activities of each agent are modeled using the unified modeling language (UML). Then, relationships among agents, working mechanisms of each agent, and several fractal-specific characteristics (self-similarity, self-organization, and goal-orientation) are modeled using the UML. Then, a method for dealing with several types of information such as products, orders, and resources in the FrMS is presented. Finally, a preliminary prototype for the FrMS using Aglets™ is presented.

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).

A Generic MMS–Based Holon Structure

Abstract This paper is about decentralised intelligent manufacturing systems, with the specific aim of proposing a generic Manufacturing Message Specification (MMS) based holon which can be used to control different manufacturing devices with simple reconfigurations. MMS is avendor–independent communication protocol for manufacturing devices and is used as a tool to control heterogeneous manufacturing devices. The generic MMS–based holon structure was implemented in the Microsoft Windows environment and incorporates stand–alone devices such as a robot or a CNC Lathe into a networked environment. The outcome of the research shows that the MMS protocol is suitable for generating modular mini–structures to implement holonic, biologically oriented and fractal manufacturing systems.