Makespan minimization for m-machine permutation flowshop scheduling problem with learning considerations

Increased complexity of current manufacturing systems together with dynamic conditions and permanent demands for flexible and robust functionality makes their management and control very difficult and challenging. Workflow simulation is an effective approach to investigate dynamic workflow scheduling policies and evaluate the overall manufacturing system performance. The results attained in simulation model can give directions on how to maximize system output when selecting an appropriate scheduling practice for a real system. In this paper, we investigate the abilities of multi-agent systems in combination with dynamic dispatching rules and failure handling mechanisms to manage dynamic environment conditions (such as machine failures) for systems in the production automation domain. We measure system robustness by systematically assessing the total system performance (e.g., number of finished products) in a number of representative test cases. We use an agent-based simulation environment, MAST, which has been validated with real-world hardware to strengthen the external validity of the simulation results. We investigated the performance of a re-scheduling component which uses four different policies that define how to adjust the system schedule in case of machine disturbances/failures. In the context of the empirical study the Complete Rerouting re-scheduling policy outperformed all other policies.     

Controllable processing time policies for job shop manufacturing system

The research presented concerns the policy to manage a job shop in which the machines have controllable processing times. A controllable processing time means that it can be reduced processing time by using additional resources. The model proposed is based on a multi-agent architecture that supports the manufacturing system. The policy proposed concerns the evaluation of the workload of the resources. It is necessary to define the following issues for the controllable time process of a resource: the condition of start and the duration of the process time reduction. Two approaches are proposed to assign the resources to the machines. The first approach concerns the reduction of the processing time one machine at time, while the second approach distributes the additional resources proportionally among the machines. A simulation environment is developed to test the proposed approach in several dynamic conditions. The simulation results show that the control of the processing times proposed allows to improve significantly the performance.     

协同制造网络中基于知识的风险控制体系研究

为解决协同制造网络在复杂分布环境中的风险管理问题,需要建立一个稳定、集成的风险控制系统.分析了协同生产过程中的风险控制问题,指出基于知识的风险控制机制在协同制造网络中所起的重要作用.建立基于Agent的风险控制过程模型来适应动态分布的协同生产环境,并对模型中风险知识库的构成进行了说明.建立一种基于公共对象请求代理(CORBA)和工作流技术的风险控制体系框架,以一种过程框架的方法很好地解决了协同制造网络中风险的识别以及风险集中与分布控制问题.最后,介绍系统的实现与功能.     

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.     

Adaptive production control system for a flexible manufacturing cell using support vector machine-based approach

Real-time adaptive production control in the flexible manufacturing cell (FMC) is a complex issue that needs to be addressed to realize good performance and high productivity. In this paper, we have considered a support vector machine (SVM)-based simulation approach to resolve a production control problem in an FMC that operates in a dynamic environment. A SVM-based simulation approach chooses the most relevant scheduling rule out of several predefined ones on the basis of the current states of the system. This paper examines and compares the performance of the SVM-based simulation approach with the competent scheduling rules under two different operational environments which are characterized by the uncertainty of demand. We have also developed a Visual Basic-based simulation approach for scheduling of component parts in the context of FMC under different situations. The SVM methodology to control the production offers better performance than the single-rule-based production control system.     

Production Capacity of Flexible Manufacturing Systems with Fixed Production Ratios

Determining the production capacity of flexible manufacturing systems is a very important issue in the design of such systems. We propose an approach for determining the production capacity (i.e., the maximum production rate) of a flexible manufacturing system with several part types, dedicated pallets, and fixed production ratios among the different part types. We show that the problem reduces to the determination of a single parameter for which we propose an iterative procedure. Simulation or approximate analytical techniques can be used as the building block performance evaluation technique in the iterative procedure.     

Modelling and Simulation of Integrated Operations and Information Systems in Manufacturing

This paper presents a novel method to determine the relative impact on logical interactions and interrelationships between operations and information systems within a manufacturing environment by formulating an integrated model, in which both operational function and information processing function are modelled and simulated to predict system behaviour and to obtain an optimal solution that maximises system performances. To achieve this, modelling and simulation of a flexible printed circuit board assembly (PCBA) system has been implemented. The research has shown that applying this approach is valuable for analysing a wide range of manufacturing systems (CIM, FMS, dynamic process control systems, etc.).     

Development and evaluation of feature-focused dynamic routing policy

This paper reports on a development of feature-focused dynamic routing policy and its evaluation in a flexible manufacturing systems (FMS) simulation framework. The dynamic policy is based on an integrative methodology in which process planning system IMPlanner is integrated with FMS simulation module. IMPlanner’s rule-based system process selection system performs knowledge-intensive task of generating alternative processing options for each feature for parts in production plan. Generated alternative routings (process plan network) for each part are utilized in the FMS simulation module such that routing decision in FMS are made on periodic intervals by considering alternative processes for each feature and making decision based on the current system status and performance. The proposed framework has been evaluated in an experimental FMS simulation module, implemented in Arena, in which two performance criteria, machine utilization and WIP, were used to make routing decisions. The feature-focused approach is compared with traditional static decision-making, and its improved performance is demonstrated.     

A game theoretic coordination for trading capacity in multisite factory environment

Multisite factories geographically distributed often have to implement an opportune tool to integrate their resources and demand forecasts in order to gather a specific production objective. The proposed research develops a distributed approach, for a network of independent enterprises, able to facilitate the capacity process by using a multiagent architecture and a cooperative protocol. The last one is based on game theory and, in particular, on Nash bargaining solution. Moreover, a discrete simulation environment has been developed to compare the proposed approach with the one in which no cooperation among enterprises exist. Several simulation scenarios were conducted to analyze the performances’ trends in various environment conditions. The goal has been the evaluation of the unallocated capacity, the unsatisfied demand, the profits generated by the network, the distribution of the transactions among the plants, and the number of activated links among plants. The simulation results show that the proposed approach leads to a better performance indexes and more relevant benefits when the dynamicity of the environment growths.     

Customer-focused and product-line-based manufacturing performance measurement

Until the 1980s, manufacturing companies relied solely on performance measurement systems based on traditional cost accounting systems to control, monitor, and improve operations. However, it has been shown that these systems do not capture the relevant performance issues for today’s manufacturing environment. Pre-80s systems focused on monitoring and controlling instead of supporting process improvements, promoting overall system optimization and addressing the dynamics of changing systems. A variety of integrated systems were proposed to overcome the limitations of the traditional performance measurements systems. However, these systems have not yet fully addressed the performance measurement system requirements for today’s manufacturing environment. This paper presents an integrated dynamic performance measurement system (IDPMS) developed in conjunction with the D Company Plant of Chungli, Taiwan. IDPMS integrates three main areas; company management, process improvement, and the factory shop floor. To achieve an integrated system, these three areas are linked through specifications, reporting and dynamic defined success area updating, performance measures, and performance standards. This study is undertaken to specify the interaction and movement among the three groups in the process from production planning to customer, “planning-manufacturing-customer”. The results from these stages, production planning, manufacturing, and customer service, are integrated. These factors are transformed into measurable, quantitative, and JIT (just-in-time) parameters utilized along with management by objectives (MBO) principles in planning and establishing a manufacturing performance measurement system focused on satisfying both internal and external customers. An example is given that illustrates how the IDPMS addresses the current performance measurement system requirements.     

基于内分泌调节原理的制造任务与资源动态协调机制研究

针对制造系统在动态环境下的任务与资源协调优化问题,在保证按时完工的前提下,分析了制造任务与资源协调优化过程,建立了数学模型。受人体内分泌调节机制的启发,设计了两种可以相互影响的激素(任务相关激素和资源相关激素),同时,考虑到突发事件对制造系统工作性能的影响,提出了基于激素的资源与任务的动态协调算法。实例验证表明,该算法切实可行,具有任务分配质量高、动态协调性能好、协调过程通信量小、控制系统鲁棒性较好等优点。     

An architecture for a shop-floor controller using colored Petri nets

In a dynamic and flexible manufacturing environment, a shop-floor controller must be designed so that it automatically (or with minimum human intervention) and quickly responds to the changes (e.g., in part type or part routing) in the system. Such a performance may be achieved provided that the controller is simple and sufficiently general in its scope of application. In this article, we present an architecture for such a shop-floor controller. The architecture is based on colored Petri nets with ordered colored sets and structured input and output functions.     

基于自适应遗传算法的柔性动态调度研究

提出了柔性生产环境下动态调度系统的框架结构。系统主要由评估模块，动态数据库管理模块以及遗传算法模块组成，它能够在扰动发生后快速提供新的调度计划；而自适应策略保证遗传算法有很好的收敛速度与精度。该方案减少了人为的干预，完全可以在实时生产条件下运行。     

An Investigation of Stochastic Analysis of Flexible Manufacturing Systems Simulation

This paper describes the use of an ARIMA (autoregressive-integrated- moving-average) model and its equivalent state space models to produce rule-based knowledge for flexible manufacturing systems (FMS) that can be used to investigate a wide variety of problems including machine breakdown, material shortage, and changes of scheduling rules. One great advantage of using the proposed models is the ease with which the simulation results can be summarised, analysed and captured, as well as the availability of the mathematical representation of the knowledge that can be kept in a knowledge database for evaluation and selection of alternative FMS strategies in a real-time environment. Various case studies are used to illustrate the methodology and the development of ARIMA and state space models, the analysis includes the system cost and stability of changes or interventions, the relationships among the simulation inputs and outputs, and the formulation of the production rule-base for the FMS scheduler. Management can use this integrated approach to describe and predict the dynamic behaviour of a complex FMS.     

Production activity control: A practical approach to scheduling

There is a widely perceived gap within the domain of scheduling for manufacturing systems, namely, many of the methods employed by production supervisors are quite different from those developed by researchers. In a sense, this inconsistency highlights the important fact that much scheduling research has failed to win approval where it matters most, namely, within the manufacturing system.In this article, we argue for a practical approach to scheduling for manufacturing systems, one that we believe can narrow, and possibly bridge, the gap between theory and practice. This approach is based upon a well-defined and modular architecture for scheduling, termedproduction activity control. This architecture is the foundation of our proposed solution to scheduling, since it provides a coherent blueprint for the synthesis of information technology and scheduling strategies. The result of this synthesis is a design tool for production activity control, which allows for detailed and disciplined experimentation with a range of scheduling strategies in a controlled and simulated environment. Due to the unique modular property of the design tool, these strategies may then be implemented live in a flexible manufacturing facility, hence narrowing the gap between scheduling theory and manufacturing practice. Our overall approach is tested through an appropriate implementation in a modern electronics assembly plant.     

Performance management of manufacturing system networks

Performance management of communication networks is critical for speed, reliability, and flexibility of information exchange between different components, subsystems, and sectors (e.g., factory, engineering design, and administration) of production process organizations in the environment of computer integrated manufacturing (CIM). Essential to this distributed total manufacturing system is the integrated communications network over which the information leading to process interactions and plant management and control is exchanged. Such a network must be capable of handling heterogeneous traffic resulting from intermachine communications at the factory floor, CAD drawings, design specifications, and administrative information. The objective is to improve the efficiency in handling various types of messages, e.g., control signals, sensor data, and production orders, by on-line adjustment of the parameters of the network protocol.This paper presents a conceptual design, development, and implementation of a network performance management scheme for CIM applications including flexible manufacturing. The performance management algorithm is formulated using the concepts of: (1) Perturbation analysis of discrete event dynamic systems; (2) stochastic approximation; and (3) learning automata. The proposed concept for performance management can also serve as a general framework to assist design, operation, and management of flexible manufacturing systems.The performance management procedure has been tested via emulation on a network test bed that is based on the manufacturing automation protocol (MAP) which has been widely used for CIM networking. The conceptual design presented in this paper offers a step forward to bridging the gap between management standards and users' demands for efficient network operations since most standards such as ISO and IEEE address only the architecture, services, and interfaces for network management.This work was supported in part by National Science Foundation under Research Grant No. DDM-90-15173.     

Deadlock prevention and avoidance in FMS: A Petri net based approach

The use of structure theory of Petri nets to develop efficient deadlock prevention and deadlock avoidance methods for flexible manufacturing systems (FMSs) modelled by S⁴R nets is demonstrated. Major synchronisation patterns, such as generalised parallel and sequential mutual exclusion, frequently observed in FMS contexts can be represented by this class. The liveness property of a given S⁴R net (deadlock-freeness in the context of FMSs) is characterised in terms of structural Petri net elements called siphons. An efficient method for controlling minimal siphons of a given S⁴R net is developed where local control places are added to the net. A sufficient condition for liveness of the augmented net is provided. This constitutes a deadlock prevention approach. When the net liveness condition is not satisfied, an on-line controller, using a dynamic resource allocation policy, is developed for the augmented net. The performance of the proposed approaches is illustrated using several examples.     

The Applications of Flexible Manufacturing Technologies in Business Process Reengineering

Through radical redesign of business processes and systems, policies, and organizational structures, the business process reengineering (BPR) effort was initiated in the manufacturing industry to seek performance breakthroughs. This paper describes a novel approach to the BPR, which applies flexible manufacturing systems (FMSs) design and analysis technologies, such as simulation, multicriteria decision support, and artificial intelligence (AI). These technologies are integrated to design and analyze specific FMS models related to the proposed technical and managerial changes in an industrial case. First, the literature is reviewed to obtain an understanding of the BPR concept and the role of FMS design and analysis in BPR. Second, a decision-making support system is developed to illustrate how the FMS design and analysis would affect BPR. Finally, a summary of the integrated approach practice in industry and conclusions are presented. The paper shows that the key to a successful BPR approach is the identification and analysis of specific proposed models. It also demonstrates that the integrated approach enables engineers to improve the efficiency of BPR.     

A mixed dispatching rule approach in FMS scheduling

Short-term scheduling in flexible manufacturing systems (FMSs) is a difficult problem because of the complexities and dynamic behavior of FMSs. To solve this problem, a dispatching rule approach is widely used. In this approach, however, a single dispatching rule is usually assigned for all machines in a system during a given scheduling interval. In this paper, a mixed dispatching rule which can assign a different dispatching rule for each machine is proposed. A search algorithm which selects an appropriate mixed dispatching rule using predictions based on discrete event simulation is developed for this approach. The search algorithm for the mixed dispatching rule is described in detail. The effectiveness (in meeting performance criteria) of the mixed dispatching rule and the efficiency of the search algorithm relative to exhaustive search (complete enumeration) is demonstrated on an FMS model. The mixed dispatching rule approach performs up to 15.9% better than the conventional approach, and is 4% better on average. The statistical significance of the results is dicussed.     

Application of an efficient modified particle swarm optimization algorithm for process planning

In the modern manufacturing system, many flexible manufacturing system and NC machines are introduced to improve the production efficiency. Therefore, most parts have a large number of flexible process plans. However, a part can use only one process plan in the manufacturing process. So, the process planning problem has become a crucial problem in the manufacturing environment. It is a combinatorial optimization problem to conduct operations selection and operations sequencing simultaneously with various constraints deriving from the practical workshop environment as well as the parts to be processed. It is a NP-hard problem. In order to solve this problem effectively, this paper proposes a novel modified particle swarm optimization (PSO) algorithm to optimize the process planning problem. To improve the performance of the approach, efficient encoding, updating, and random search methods have been developed. To verify the feasibility and effectiveness of the proposed approach, seven cases have been conducted. The proposed algorithm has also been compared with the genetic algorithm and simulated annealing algorithm. The results show that the proposed modified PSO algorithm can generate satisfactory solutions and outperform other algorithms.