Investigating optimal capacity scalability scheduling in a reconfigurable manufacturing system

Responsiveness to dynamic market changes in a cost-effective manner is becoming a key success factor for any manufacturing system in today’s global economy. Reconfigurable manufacturing systems (RMSs) have been introduced to react quickly and effectively to such competitive market demands through modular and scalable design of the manufacturing system on the system level, as well as on the machine components’ level. This paper investigates how RMSs can manage their capacity scalability on the system level in a cost-effective manner. An approach for modeling capacity scalability is proposed, which, unlike earlier approaches, does not assume that the capacity scalability is simply a function of fixed increments of capacity units. Based on the model, a computer tool that utilizes a genetic algorithm optimization technique is developed. The tool aids the systems’ designers in deciding when to reconfigure the system in order to scale the capacity and by how much to scale it in order to meet the market demand in a cost-effective way. The results showed that, in terms of cost, the optimal capacity scalability schedules in an RMS are superior to both the exact demand capacity scalability approach and the approach of supplying all required capacity at the beginning of the planning period, which is adopted by flexible manufacturing systems (FMSs). The results also suggest that the cost-effective implementation of an RMS can be realized through decreasing the cost of reconfiguration of these new systems.     

Dynamic cellular manufacturing systems design��a comprehensive model

This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment. The proposed model, to the best of the author??s knowledge, is the most comprehensive model to date with more integrated approach to the DCMSs. The proposed DCMS model integrates concurrently the important manufacturing attributes in existing models in a single model such as machine breakdown effect in terms of machine repair cost effect and production time loss cost effect to incorporate reliability modeling; production planning in terms of part inventory holding, part internal production cost, and part outsourcing; process batch size; transfer batch size for intracell travel; transfer batch size for intercell travel; lot splitting; alternative process plan, and routing and sequence of operation; multiple copies of identical copies; machine capacity, cutting tooling requirements, work load balancing, and machine in different cells constraint; machine in same cell constraint; and machine procurements and multiple period dynamic cell reconfiguration. Further, the objective of the proposed model is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads, etc. ,in an integrated manner. Nonlinear terms of objective functions are transformed into linear terms to make mixed-integer linear programming model. The proposed model has been demonstrated with several problems, and results have been presented accordingly.     

Design principles of reconfigurable machines

Reconfigurable machines form a new class of machines that are designed around a specific part family of products and allow rapid change in their structure. They are designed to allow changes in machine configuration according to changes in production requirements. The reconfiguration may be related to changes in machine functionality or its scalability, i.e., the change in production volumes or speed of operation. Reconfigurable machines represent a new class of machines that bridges the gap between the high flexibility and high cost of totally flexible machines and the low flexibility and low cost of fully dedicated machines. The design principles of reconfigurable machines follow a similar philosophy, which was derived for reconfigurable manufacturing systems, and present an approach for the design of machines to be used mainly in high-volume production lines. This paper introduces design principles for reconfigurable machines, which may be applied in different fields of manufacturing. Based on these design principles, three types of reconfigurable machines were designed for various types of production operations such as: machining, inspection and assembly. This paper shows how the suggested design principles were utilized in the design of several full-scale machine prototypes and tested experimentally.     

Flexible and reconfigurable manufacturing systems paradigms

Reconfigurable Manufacturing System (RMS) is a new manufacturing systems paradigm that aims at achieving cost-effective and rapid system changes, as needed and when needed, by incorporating principles of modularity, integrability, flexibility, scalability, convertibility, and diagnosability. RMS promises customized flexibility on demand in a short time, while Flexible Manufacturing Systems (FMSs) provides generalized flexibility designed for the anticipated variations and built-in a priori. The characteristics of the two paradigms are outlined and compared. The concept of manufacturing system life cycle is presented. The main types of flexibility in manufacturing systems are discussed and contrasted with the various reconfiguration aspects including hard (physical) and soft (logical) reconfiguration. The types of changeability and transformability of manufacturing systems, their components as well as factories, are presented along with their enablers and compared with flexibility and reconfigurability. The importance of having harmonized human-machine manufacturing systems is highlighted and the role of people in the various manufacturing paradigms and how this varies in pursuit of productivity are illustrated. Finally, the industrial and research challenges presented by these manufacturing paradigms are discussed.     

Optimal configuration selection for Reconfigurable Manufacturing Systems

The selection of Reconfigurable Manufacturing Systems (RMS) configurations that include arrangement of machines, equipment selection, and assignment of operations, has a significant impact on their performance. This paper reviews the relevant literature and highlights the gaps that exist in this area of research. A novel “RMS Configuration Selection Approach” is introduced. It consists of two phases; the first deals with the selection of the near-optimal alternative configurations for each possible demand scenario over the considered configuration periods. It uses a constraint satisfaction procedure and powerful meta-heuristics, real-coded Genetic Algorithms (GAs) and Tabu Search (TS), for the continuous optimization of capital cost and system availability. The second phase utilizes integer-coded GAs and TS to determine the alternatives, from those produced in the first phase, that would optimize the degree of transition smoothness over the planning horizon. It uses a stochastic model of the level of reconfiguration smoothness (RS) across all the configuration periods in the planning horizon according to the anticipated demand scenarios. This model is based on a RS metric and a reconfiguration planning procedure that guide the development of execution plans for reconfiguration. The developed approach is demonstrated and validated using a case study. It was shown that it is possible to provide the manufacturing capacity and functionality needed when needed while minimizing the reconfiguration effort. The proposed approach can provide decision support for management in selecting RMS configurations at the beginning of each configuration period.

制造系统的可重构性

可重构制造模式是一种指导管理和控制制造系统重构过程的制造哲理,它使制造系统有效地响应不断变化的环境,制造系统具有可重构能力是其生存和发 基本手段,具有较高可重构笥的公司在风云突变的环境中将远远超过其竞争对手。本文探讨了可重构造模式的基本定义和内涵,并从组织、过程、产品加工系统和信息平台等五个方面研究了制造系统的可重构性。     

Optimization of the multi-objective dynamic cell formation problem using a scatter search approach

This paper addresses the dynamic cell formation (DCF) problem with multiple conflicting objectives. Recent researches have mainly focus on single-objective cell formation procedures that deals with the identification of part families and associated machine groups for constant demands. However, varying market demands and fluctuations of the business environment have caused cellular manufacturing systems to operate under dynamic conditions. Thus, the optimal configuration of manufacturing cells in each period is different and the reconfiguration of cells is required. This paper proposes a nonlinear multi-objective mathematical model of the DCF problem by giving weighing to three conflicting objectives including the machine relocation cost in the process of reconfiguring cells, the utilization rate of machine capacity, and the total number of intercell moves over the entire planning horizon. To solve the nonlinear multi-objective model, a scatter search approach is developed, which redesigns the common components of scatter search and incorporates diversification generator, global criterion method, local search method, and other improvement mechanisms to provide a wide exploration of the search space through intensification and diversification. The proposed approach is compared with the commercial solver CPLEX on 10 test problems, some of which are large dimensions. Computational results have demonstrated the effectiveness of the scatter search approach.     

基于敏捷制造单元的车间动态重构

为适应现代车间的敏捷化需求,提出了一种基于敏捷制造单元的车间动态重构方法.车间的动态重构是一个优化制造资源,进而构造面向产品的敏捷制造单元,形成虚拟车间的过程,采用数学规划和模糊理论相结合的方法,优化制造资源.同时,提出了一种基于不完全知识和进化博弈理论的动态单元重构模型,它能够面向不确定的需求目标,采用自下而上和自上而下相结合的方法,快速生成稳定优化的可重构制造单元,从而实现敏捷车间的组织再设计.该模型求解采用协同进化算法,并通过实例,验证了该方法的可行性和有效性.     

Capacity reconfiguration management in reconfigurable manufacturing systems

During a manufacturing operation, exceptions may occur dynamically and unpredictably. Their occurrence may lead to the degradation of system performance or, in the worst case scenario, may interrupt the production process. The research proposes a multi-agent architecture for the capacity reconfiguration problem in a reconfigurable manufacturing system (RMS). A policy to manage capacity exchange among manufacturing lines based on due date performance is proposed. The Multi-Agent architecture was built in a simulation environment developed in ARENA^® package and it is compared with a dedicated manufacturing and flexible manufacturing systems. The simulations are conducted in several demand scenarios to test the approach in a static and dynamic context. The simulation environment developed can support the planner to decide among the different manufacturing systems by the evaluation of the manufacturing performance. The simulation results, in dynamic environment, showed that the proposed approach leads to similar performance to flexible manufacturing system.     

可重构制造单元控制系统设计

网络化制造将是信息时代的主要生产模式 ,制造系统可重构是网络化制造的关键单元技术。在分析了网络化制造环境对可重构制造系统体系结构要求的基础上 ,提出了一种支持制造系统可重构的单元控制器设计方案 ,并详细介绍了该控制器的软件框架结构、功能模块和实现技术。     

An integrated model of dynamic cellular manufacturing and supply chain system design

In a global dynamic environment, there is a need to develop organizations and facilities significantly more flexible and responsive. This work proposes an integrated model of dynamic cellular manufacturing and supply chain design with consideration of various issues such as multi-plant locations, multiple markets, multi-time periods, reconfiguration, etc. The model objective was to minimize the sum of various costs such as facility/plant to market transportation cost, part holding cost at a facility/plant, part outsourcing cost, machine procurement cost, machine maintenance overhead cost, machine repair cost, production loss cost due to machine breakdown, machine operation cost, setup cost, tool consumption cost, inter-cell travel cost, intra-cell travel cost, and system reconfiguration cost for the entire planning time horizon. To study the model, three procedures—LINGO, artificial immune system, and hybrid artificial immune system—are used to perform computational experiment on some problems from existing literature. The best result generally is found by the hybrid artificial immune system algorithm.     

面向多品种变批量的可重构制造系统的设计方法研究

可重构制造系统的设计目标是要确定各种零件的生产周期、各种零件之间的生产顺序与加工各种零件所用的组态。建立了各生产周期成本模型、重构成本模型与全生产周期成本模型。由各种零件的批量确定加工各种零件的标准生产周期，分析系统成本冗余，得到了多组偏差生产周期，求出了各种生产周期下各种零件之间所有生产排序的K-优组态路径。通过比较所求得的组态路径，可以获得一条最优与多条次优组态路径。用案例验证了所提出的方法。     

Models for capacity acquisition decisions considering operational costs

In this article, we study a capacity acquisition problem by considering technology choice and operational factors in a stochastic environment. The motivation for our work comes from developments in modern flexible technologies and a problem encountered in a real industrial setting. We study the impact of operational factors such as setup times, demand patterns, and inventory/back order costs on the decisions of capacity acquisition and technology choice. We consider three alternatives in capacity and technology decisions: (i) a flexible system, (ii) a dedicated system, and (iii) a combination of these two systems. For each system, we develop a model that integrates investment decisions and operational decisions to determine an optimal amount of capacity to purchase and the time and the types of parts to produce. The objective is to minimize the capacity acquisition cost at the beginning of the planning horizon and the total expected operational costs over an infinite planning horizon. To solve the problem in this article, a solution procedure is proposed. Managerial insights are also derived from extensive computational results.     

CONCURRENT PRODUCT PORTFOLIO PLANNING AND MIXED PRODUCT ASSEMBLY LINE BALANCING

Reconfigurable products and manufacturing systems have enabled manufacturers to provide "cost effective" variety to the market. In spite of these new technologies, the expense of manufacturing makes it infeasible to supply all the possible variants to the market for some industries. Therefore, the determination of the right number of product variants to offer in the product portfolios becomes an important consideration. The product portfolio planning problem had been independently well studied from marketing and engineering perspectives. However, advantages can be gained from using a concurrent marketing and engineering approach. Concurrent product development strategies specifically for reconfigurable products and manufacturing systems can allow manufacturers to select best product portfolios from marketing, product design and manufacturing perspectives. A methodology for the concurrent design of a product portfolio and assembly system is presented. The objective of the concurrent product portfolio planning and assembly system design problem is to obtain the product variants that will make up the product portfolio such that oversupply of optional modules is minimized and the assembly line efficiency is maximized. Explicit design of the assembly system is obtained during the solution of the problem. It is assumed that the demand for optional modules and the assembly times for these modules are known a priori. A genetic algorithm is used in the solution of the problem. The basic premise of this methodology is that the selected product portfolio has a significant impact on the solution of the assembly line balancing problem. An example is used to validate this hypothesis. The example is then further developed to demonstrate how the methodology can be used to obtain the optimal product portfolio. This approach is intended for use by manufacturers during the early design stages of product family design.     

A feature-based generic setup planning for configuration synthesis of reconfigurable machine tools

Reconfigurable machine tool (RMT) plays a vital role in reconfigurable manufacturing systems creating modularity, convertibility, reusability, and scalability in systems. RMT also needs to be characterized for multiple spindle orientations. Different tool positioning requirements (spindle orientations) arising with a part or a part family can be associated to synthesize and customize the RMT configuration. In this paper, we have proposed a new approach of generic setup planning (GSP) for RMT configuration synthesis. From the feature-based computer-aided design data, machining features are grouped according to their tool approach direction in GSP. To support its implementation, an enriched machining feature definition is also introduced. A new algorithm is developed for automating GSP generation and verified against a standard case study.     

Assessment of manufacturing systems reconfiguration smoothness

The effect of the configuration selection on the smoothness and easiness of manufacturing systems reconfiguration process cannot be neglected, especially when dealing with reconfigurable manufacturing systems (RMS). The term “reconfiguration smoothness” is introduced in this paper to address this issue. In order to evaluate the level of reconfiguration smoothness (RS), a metric was developed to provide a relative measure of the expected cost, time, and effort required to convert from one configuration to another. This metric is composed of three components representing different levels of reconfiguration, namely; market-level reconfiguration smoothness (TRS), system-level reconfiguration smoothness (SRS), and machine-level reconfiguration smoothness (MRS). Rules are introduced to guide the development of execution plans for system-level reconfiguration, which we call “reconfiguration planning”. These plans help reduce the physical effort of reconfiguring the system. A case study is presented to demonstrate the use of the developed metric followed by sensitivity analysis to show the effect of changing different metric parameters. The results show how the developed metric provides a powerful relative assessment tool for the transitional smoothness between a current configuration and a number of candidate feasible configurations for the next period. This can affect the configuration selection decisions at the beginning of each configuration period.     

基于多Agent的车间重构模型

指出了敏捷制造模式下 ,车间的功能除了具有常规的生产管理和控制功能外 ,还具有实现单元动态重构的功能和通过网络对外合作功能。提出了基于多 Agent的车间动态重构模型 ,分析了模型中 Agent之间的协商机制和实现车间动态重构模型的支撑技术     

A methodology to define a reconfigurable system architecture for a compact heat exchanger assembly machine

Due to the unexpected, fast, and constant changes of market requirements and the hypercompetency, robust manufacturing systems are needed that adjust easily to operational variability and the customized product supply. The simply substitution of components, software, hardware, and/or their adaptation by parameters resetting are an attractive option to face this challenge. Short product life cycles are an undeniable consequence and evidence of this. For this reason, to develop products or services profitably in the product manufacturing field, it is common to use the product family concept, which involves sharing components, functional features, and manufacturing process, both to make a cheaper product development process and to obtain customized products. A new generation of manufacturing systems that deploy characteristics such as adaptability and flexibility responding to the market dynamics called reconfigurable manufacturing systems (RMS) are required by market according to manufacturing experts. The manufacturing systems with modular architecture are the best way to meet flexible and adaptable RMSs because they allow reconfiguration by a simple module substitution or by resetting module operation parameters. This paper presents a design methodology developed to obtain modular RMS. The method integrates the utilization of modular architecture principles, selection algorithms (analytical hierarchical process), clustering algorithms (average linkage clustering algorithm), family product features and functional system analysis in the classical product design process. The methodology proposed allows defining the most adequate modular system architecture and the modular definition of the reconfiguration variables that are needed to reach the flexibility required. A real study case about a heat exchanger assembly machine is presented where this methodology is applied in order to present an evidence of its usefulness.     

Equipment ontology for modular reconfigurable assembly systems

Evolvable and Reconfigurable Assembly Systems (RAS) enable enterprises to rapidly respond to changes in today’s increasingly volatile and dynamic global markets. One of the key success factors for the effective use of RAS is methods and tools that can rapidly configure and reconfigure assembly systems driven by changing requirements. The focus of this paper is the development of a suitable equipment model to support the effective design of reconfigurable assembly systems. The work has been motivated by the need to provide solutions for increasing product customisation and volume changes over the product life-cycle that directly impact on the final product assembly. The paper proposes a comprehensive equipment ontology to enable effective decision-making during the design and evaluation of new RAS configurations. The proposed ontology is based on the function-behaviour-structure paradigm, and is formalised to facilitate its application in distributed web-enabled decision-making environments. The equipment configuration and reconfiguration approach and prototype decision-making environment are illustrated using system design examples.     

可重构装配系统中智能体的开发

为了实现可重构装配系统的快速重构能力,在分析了传统控制结构的基础上,结合分层递阶和分布式控制的优点,提出了基于多智能体系统的混合控制体系结构。这种结构具有低复杂性、强鲁棒性、易维护性、可扩展性以及可重用性等特点,能够适应重构系统的要求。在遵守智能物理代理基金会规范的前提下,以Java智能体开发平台进行了装配系统中各层智能体的实例开发。