Scalability planning for reconfigurable manufacturing systems

Scalability is a key characteristic of reconfigurable manufacturing systems, which allows system throughput capacity to be rapidly and cost-effectively adjusted to abrupt changes in market demand. This paper presents a scalability planning methodology for reconfigurable manufacturing systems that can incrementally scale the system capacity by reconfiguring an existing system. An optimization algorithm based on Genetic Algorithm is developed to determine the most economical way to reconfigure an existing system. Adding or removing machines to match the new throughput requirements and concurrently rebalancing the system for each configuration, accomplishes the system reconfiguration. The proposed approach is validated through a case study of a CNC-based automotive cylinder head machining system.     

Trends and perspectives in flexible and reconfigurable manufacturing systems

To better understand future needs in manufacturing and their enabling technologies, a survey of experts in manufacturing has been conducted. The survey instrument (i.e., questionnaire) tries to assess the experience to date with the use of flexible manufacturing systems (FMS) and to examine the potential roles and enabling technologies for reconfigurable manufacturing systems (RMS). The results show that two-thirds of respondents stated that FMSs are not living up to their full potential, and well over half reported purchasing FMS with excess capacity (which was eventually used) and excess features (which in many cases were not eventually used). They identified a variety of problems associated with FMS, including training, reconfigurability, reliability and maintenance, software and communications, and initial cost. However, despite these issues, nearly 75% of respondent expressed their desire to purchase additional, or expand existing FMSs. The experts agreed that RMS (which can provide exactly the capacity and functionality needed, exactly when needed) is a desirable next step in the evolution of production systems. The key enabling technologies for RMS were identified as modular machines, open-architecture controls, high-speed machining, and methods, training and education for the operation of manufacturing systems.     

Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation

Cloud-based design manufacturing (CBDM) refers to a service-oriented networked product development model in which service consumers are enabled to configure, select, and utilize customized product realization resources and services ranging from computer-aided engineering software to reconfigurable manufacturing systems. An ongoing debate on CBDM in the research community revolves around several aspects such as definitions, key characteristics, computing architectures, communication and collaboration processes, crowdsourcing processes, information and communication infrastructure, programming models, data storage, and new business models pertaining to CBDM. One question, in particular, has often been raised: is cloud-based design and manufacturing actually a new paradigm, or is it just “old wine in new bottles”? To answer this question, we discuss and compare the existing definitions for CBDM, identify the essential characteristics of CBDM, define a systematic requirements checklist that an idealized CBDM system should satisfy, and compare CBDM to other relevant but more traditional collaborative design and distributed manufacturing systems such as web- and agent-based design and manufacturing systems. To justify the conclusion that CBDM can be considered as a new paradigm that is anticipated to drive digital manufacturing and design innovation, we present the development of a smart delivery drone as an idealized CBDM example scenario and propose a corresponding CBDM system architecture that incorporates CBDM-based design processes, integrated manufacturing services, information and supply chain management in a holistic sense.     

A conceptual framework for agent-based agile manufacturing cells

Abstract. Agile manufacturing techniques are perceived as the manufacturing systems of the future. Agile manufacturing cells are dynamic and reconfigurable and the modelling of the manufacturing cells and its interaction mechanism is critical to its successful use. This paper deals with the architecture and cooperation mechanism of web‐based agile manufacturing cells. Based on an analysis of structure and organization requirements of agile manufacturing cells and a comparison of three basic architectures of manufacturing systems, the quasi‐heterarchical architecture is used for the agile manufacturing cell. Functional layers are defined in this architecture to make the cell's control system reconfigurable and reusable. Agent technology is adopted for implementation of each layer's functions to establish an agent‐based model of agile manufacturing cells. Four types of agents including cooperation agent, job management agent, resource broker agent, and resource control agent are defined, and their functions discussed. Finally, a real time interaction mechanism of the agents is presented by considering the activities during the agents’ cooperation in an agile manufacturing cell.     

An object-oriented framework for developing distributed manufacturing architectures

Management of complexity, changes and disturbances is one of the key issues of production today. Distributed, agent-based structures represent viable alternatives to hierarchical systems provided with reactive/proactive capabilities. In the paper, approaches to distributed manufacturing architectures are surveyed, and their fundamental features are highlighted, together with the main questions to be answered while designing new structures. Moreover, an object-oriented simulation framework for development and evaluation of multi-agent manufacturing architectures is introduced.     

计算机辅助可重构制造系统设计

可重构制造系统是为了快速而准确地提供响应新的高层需求所需的生产能力和生产同一零件族内的新零件所需的制造功能，从一开始就设计成可面向系统级和生产资源级快速而又以有竞争力的成本重构的制造系统，文中分析了可重构制造系统的设计方法及其特征，提出了计算机辅助可重构制造系统设计这一新的研究方向，说明了包括动态适应学习识别机制，建模分析与性能优化，专家系统、集成设计等模块的设计机辅助可重建制造系统设计的流程，实现了可重构制造系统的集成设计。     

Applications of agent-based systems in intelligent manufacturing: An updated review

Agent technology has been recognized as a promising paradigm for next generation manufacturing systems. Researchers have attempted to apply agent technology to manufacturing enterprise integration, enterprise collaboration (including supply chain management and virtual enterprises), manufacturing process planning and scheduling, shop floor control, and to holonic manufacturing as an implementation methodology. This paper provides an update review on the recent achievements in these areas, and discusses some key issues in implementing agent-based manufacturing systems such as agent encapsulation, agent organization, agent coordination and negotiation, system dynamics, learning, optimization, security and privacy, tools and standards.     

RMS中的基于时间的设备选择方法研究

根据生产需求快速确定制造资源是可重组制造系统高效快速响应市场变化的关键功能之一。文中提出了以系统整体加工时间消耗最少为目标的时间虚负荷矩阵算法,这种算法通过矩阵进行运算,计算简单直观,在计算过程中同时实现设备优化选择和工序分配,这种算法还可应用于车间作业调度。     

RMS design methodology for automotive framing systems BIW

Today, markets increasingly require more customized products, with shorter life cycles. In response, manufacturing systems have evolved from mass production techniques, through flexible automation and mass customization, to produce at mass production costs. Manufacturing facilities must incorporate more flexibility and intelligence, evolving toward reconfigurable manufacturing systems (RMS). RMS are amid to posses such flexibility and responsiveness and said to be the next generation of world class systems. RMS are designed for rapid change in structure and for a quickly adjustable production capacity. This paper proposes a new methodology (high level process) of framework using flexible and reconfigurable manufacturing systems principles for automotive framing systems as well as to provide a guideline to support the structure of different stages of the design methodology. The proposed methodology is presented through a case study using data based on actual production systems of three different styles; (process and design data) which supports the hypothesis of the research.     

Synchronization-oriented reconfiguration of FPAI under graduation intelligent manufacturing system in the COVID-19 pandemic and beyond

Companies with manufacturing systems that are more responsive and resilient will be able to survive or even gain market shares in the face of the unpredicted variable of an outbreak similar to the COVID-19 pandemic. Motivated by an industrial company restructuring its manufacturing system with the layout of fixed-position assembly islands (FPAI) during the COVID-19 pandemic, this paper introduces the synchronization-oriented reconfiguration of FPAI under Graduation Intelligent Manufacturing System (GiMS). Inspired by the graduation ceremony, a novel manufacturing mode-Graduation Manufacturing System (GMS) with ticket-based reconfigurable structures, is designed for organizing production operations with simplicity and resilience for the layout of FPAI. The IIoT and digital twin-enabled GiMS is developed for transforming real-time visibility in operations to support the reconfiguration of the manufacturing system. A synchronization-oriented reconfiguration mechanism is proposed to achieve the synchronous interaction among changing customer demand, island configuration, and production activities allocation rapidly and cost-effectively. Cloud services integrating the proposed reconfiguration mechanism are developed for managers and onsite operators for supporting the successful reconfiguration implementation with enhanced operational visibility. Through the case study of an industrial company, the effectiveness of the proposed concept and approach is verified.     

Agent-based distributed manufacturing control: A state-of-the-art survey

Manufacturing has faced significant changes during the last years, namely the move from a local economy towards a global and competitive economy, with markets demanding for highly customized products of high quality at lower costs, and with short life cycles. In this environment, manufacturing enterprises, to remain competitive, must respond closely to customer demands by improving their flexibility and agility, while maintaining their productivity and quality. Dynamic response to emergence is becoming a key issue in manufacturing field because traditional manufacturing control systems are built upon rigid control architectures, which cannot respond efficiently and effectively to dynamic change. In these circumstances, the current challenge is to develop manufacturing control systems that exhibit intelligence, robustness and adaptation to the environment changes and disturbances. The introduction of multi-agent systems and holonic manufacturing systems paradigms addresses these requirements, bringing the advantages of modularity, decentralization, autonomy, scalability and re-usability. This paper surveys the literature in manufacturing control systems using distributed artificial intelligence techniques, namely multi-agent systems and holonic manufacturing systems principles. The paper also discusses the reasons for the weak adoption of these approaches by industry and points out the challenges and research opportunities for the future.     

A non-dominated sorting genetic algorithm based approach for optimal machines selection in reconfigurable manufacturing environment

This paper deals with a problem of reconfigurable manufacturing systems (RMSs) design based on products specifications and reconfigurable machines capabilities. A reconfigurable manufacturing environment includes machines, tools, system layout, etc. Moreover, the machine can be reconfigured to meet the changing needs in terms of capacity and functionality, which means that the same machine can be modified in order to perform different tasks depending on the offered axes of motion in each configuration and the availability of tools. This problem is related to the selection of candidate reconfigurable machines among an available set, which will be then used to carry out a certain product based on the product characteristics. The selection of the machines considers two main objectives respectively the minimization of the total cost (production cost, reconfiguration cost, tool changing cost and tool using cost) and the total completion time. An adapted version of the non- dominated sorting genetic algorithm (NSGA-II) is proposed to solve the problem. To demonstrate the effectiveness of the proposed approach on RMS design problem, a numerical example is presented and the obtained results are discussed with suggested future research.     

Industry 4.0 smart reconfigurable manufacturing machines

This paper provides a fundamental research review of Reconfigurable Manufacturing Systems (RMS), which uniquely explores the state-of-the-art in distributed and decentralized machine control and machine intelligence. The aim of this review is to draw objective answers to two proposed research questions, relating to: (1) reconfigurable design and industry adoption; and (2) enabling present and future state technology. Key areas reviewed include: (a) RMS – fundamentals, design rational, economic benefits, needs and challenges; (b) Machine Control – modern operational technology, vertical and horizontal system integration, advanced distributed and decentralized control; (c) Machine Intelligence – distributed and decentralized paradigms, technology landscape, smart machine modelling, simulation, and smart reconfigurable synergy. Uniquely, this paper establishes a vision for next-generation Industry 4.0 manufacturing machines, which will exhibit extraordinary Smart and Reconfigurable (SR*) capabilities.     

A process-driven computing model for reconfigurable semiconductor manufacturing

Reconfigurability is essential for semiconductor manufacturing systems to remain competitive. Reconfigurable systems avoid costly modifications required to change and adapt to changes in product, production and services. A fully automated, collaborative, and integrated while reconfigurable manufacturing system proves cost-effective in the long term and is a promising strategy for the semiconductor manufacturing industry. However, there is a lack of computing models to facilitate the design and development of control and management systems in a truly reconfigurable manner. This paper presents an innovative computing model for reconfigurable systems and controlled manufacturing processes while allowing for the integration of modern technologies to facilitate reconfiguration, such as radio frequency identification (RFID) and reconfigurable field programmable gate array (FPGA). Shop floor manufacturing activities are modeled as processes from a business perspective. A process-driven formal method that builds on prior research on virtual production lines is proposed for the formation of a reconfigurable cross-facility manufacturing system. The trajectory of the controlled manufacturing systems is optimized for on-demand production services. Reconfigurable process controllers are introduced in support of the essential system reconfigurability of future semiconductor manufacturing systems. Implementation of this approach is also presented.     

Digital twins-based smart manufacturing system design in Industry 4.0: A review

A smart manufacturing system (SMS) is a multi-field physical system with complex couplings among various components. Usually, designers in various fields can only design subsystems of an SMS based on the limited cognition of dynamics. Conducting SMS designs concurrently and developing a unified model to effectively imitate every interaction and behavior of manufacturing processes are challenging. As an emerging technology, digital twins can achieve semi-physical simulations to reduce the vast time and cost of physical commissioning/reconfiguration by the early detection of design errors/flaws of the SMS. However, the development of the digital twins concept in the SMS design remains vague. An innovative Function-Structure-Behavior-Control-Intelligence-Performance (FSBCIP) framework is proposed to review how digital twins technologies are integrated into and promote the SMS design based on a literature search in the Web of Science database. The definitions, frameworks, major design steps, new blueprint models, key enabling technologies, design cases, and research directions of digital twins-based SMS design are presented in this survey. It is expected that this survey will shed new light on urgent industrial concerns in developing new SMSs in the Industry 4.0 era.     

Expert systems for manufacturing cell simulation and design

Computer Integrated Manufacturing (CIM) is approached by means of the application of Computer Aided Design (CAD), Computer Aided Manufacturing (CAM) and other CA techniques, methods and programs/program systems. These programs are often implemented as knowledge-based, or expert systems and in this way they became typical examples of engineering application of artificial intelligence. The production task of CIM systems is solved by using flexible manufacturing systems (FMSs). FMSs built up from smaller, complex units, i.e. from flexible manufacturing cells (FMCs) have several advantages. The design and the operation of manufacturing systems need new, sophisticated methods to utilize all the embedded benefits of the sophisticated and expensive elements installed for production purposes. New methods like knowledge processing technology, cooperative problem-solving techniques, etc., offer wide possibilities to design more reasonable systems. This paper describes prototype expert systems that make use of different knowledge-based tools and techniques to design (configure, reconfigure) and simulate manufacturing cells, taking into consideration technological plans and other relevant information.     

Decision-making method of reconfigurable manufacturing systems’ reconfiguration by a Gale-Shapley model

The companies need to rapid response to new product introduction, mix and demand changes to stay competitive. A reconfigurable manufacturing system can quickly react to changes in products and market. The control method to reconfigure the machines of a reconfigurable manufacturing system is crucial for the performance level. This paper proposes a reconfiguration decision-making method based on a Game-Theory algorithm, and in particular the Gale-Shapley model. A periodic review strategy is used to create two sets: one set of machine over-loaded and one set under-loaded. The Gale-Shapley model forms a coupled of over-loaded and under-loaded machines. The reconfiguration concerns the under-loaded machine of the coupled adding also the task performed by the over-loaded machine. This paper presents a simulation environment developed to evaluate the proposed method and highlight the main topics. The simulation results highlight how the game-theory approach developed improves all the performance measures with controlled number of machines’ reconfigurations.     

Complex networks in advanced manufacturing systems

In recent years, with the rapid development of manufacturing, information, and management technology, advanced manufacturing systems (AMSs) have become increasingly more and more complex, which hinders the wider applications of many key theories and technologies in AMSs. Fortunately, in the last two decades, some dramatic advances have been made in the field of statistical physics theories, along with the extensive applications of complex network. It has provided an alternative approach to analyze AMSs. Many recent studies have focused on the theory of complex networks to describe and solve complicated manufacturing problems. Based on a great number of relevant publications, this paper presents an up-to-date literature review with the identified outstanding research issues, future trends and directions. Three critical issues are summarized after this investigation: (a) the focused areas of AMSs that have deployed the theory of complex networks, (b) the addressed issues and the corresponding approaches, and (c) the limitations and directions of the existing works.     

A novel methodology to measure the responsiveness of RMTs in reconfigurable manufacturing system

Reconfigurable manufacturing systems are designed to deliver exact functionality and capacity that is needed, when it is needed. The reconfigurable machine tool (RMT) plays a pivotal role in the accomplishment of this objective through their built in modular structure consisting of basic and auxiliary modules along with the open architecture software.     

可重构制造系统可重构逻辑控制器设计与实现

针对可重构制造系统的逻辑控制问题,提出一种可重构逻辑控制器的解决方案．该逻辑控制器具有递阶分布式的控制体系结构,并根据模块化的设计思想设计成多个分离的功能模块．然后给出基于CORBA组件模型(CCM)的可重构逻辑控制器软件的开发过程．由递阶分布式体系、模块化设计和软件组件开发技术实现的可重构逻辑控制器具有快速动态重构的能力,能满足可重构制造系统逻辑控制的要求．