Production engineering-oriented virtual factory: a planning cell-based approach to manufacturing systems design

In the traditional process of designing a manufacturing system, a sequential approach treats each of the design steps individually, without considering the requirements of concurrent design activities. The lack of systematic and concurrent consideration of the interactive impact of design decisions leads to repeated and excessive changes in the design and process. To resolve this problem, this research develops a production engineering-oriented virtual factory – a planning cell-based manufacturing systems design approach. The manufacturing systems design process based on a planning cell is reengineered according to the concept of concurrent engineering. The process modeling of a production engineering-oriented virtual factory is proposed at generic and particular levels. An illustrative example of an engine assembly plant demonstrates the effectiveness of the new approach.     

A model management systems approach to manufacturing systems design

Manufacturing systems design involves the solution of a complex series of interrelated problems. This complexity will increase in the future as manufacturing practices change to meet increased global competition. Research within manufacturing systems design has mainly been focused on finding improved models for solving particular problems, or extending existing modeling techniques. This has resulted in numerous modeling tools being available to support manufacturing systems design. However, little research work has been carried out into consolidating the existing theories and models. As a result, a large body of this work has not been applied in industry.Model management has evolved as a research area which investigates methods for storing, modifying, and manipulating models. This article describes a prototype model management system for manufacturing systems design. The objective here is not to develop another decision support system for manufacturing design, but to illustrate, through the development of a prototype system, a number of key ideas of how concepts from the area of model management systems can be used to support manufacturing systems design. The prototype model management system utilizes the structured modeling framework and uses an extended version of the structured modeling language. An important aspect of the prototype model management system is the incorporation of the model development task, thus allowing the system to be easily updated and adapted. The prototype system was evaluated using a range of queueing network models for manufacturing systems design.     

A systems approach to fixture planning and design

Within the last decade, the manufacturing research community has addressed many of the micro issues of automating the fixture design process using computers. Most of this research has concentrated on the geometric and kinematic factors that determine the configuration of a computer-aided fixture design (CAFXD) system. However, before the implementation of any of the researched micro issues can be accomplished, a systematic approach to fixture planning and design must be recognised that considers the macro issues (process planning and fixture design) of the complete design to manufacturing process. In order to improve the effectiveness and implementation of researched micro issues in fixture design, a generic model of the functional activities can provide an understanding of the process and information exchanged between process planning and fixture design. This paper presents such a generic IDEF working model that promotes the functional integration of these two functions — developed from a systems perspective.     

Production planning: a DEA-based approach

In organizations with a centralized decision making environment, production usually involves the participation of more than one individual unit, each contributing in part to the total production. The planning problem involves determining the number of products to be produced by all individual units in the next season when demand changes can be forecasted. This paper introduces a data envelopment analysis approach to making future production plans in a centralized decision making environment when demand changes can be forecasted in the next production season. The approach proposed in this paper takes the size of operational units into account so that the planned production for each unit becomes proportionate to the ability of the units. A real world data set is used to illustrate the applicability of the approach.     

Production planning in virtual cell of reconfiguration manufacturing system using genetic algorithm

This paper focuses on the scheduling problem of the reconfiguration manufacturing system (RMS) for execution level, where the final objective is to output a production plan. The practical situation in Chinese factory is analyzed, and the characteristics are summarized into the contradiction between flow and job shop production. In order to handle this problem, a new production planning algorithm in virtual cells is proposed for RMS using an improved genetic algorithm. The advantages of this algorithm have three parts: (1) the virtual cell reconfiguration is formed to assist making production plans through providing relationship among task families and machines from cell formation; (2) The operation buffer algorithm is developed for flow style production in cells, which can realize the nonstop processing for flow style jobs; and (3) The multicell sharing method is proposed to schedule job shop jobs in order to fully utilize manufacturing capability among machines in multicells. Based on the above advantages, an improved genetic algorithm is developed to output scheduling plan. At last, the algorithm is tested in different instances with LINGO and the other genetic algorithm, and then the scheduling solution comparison shows the proposed algorithm can get a better optimum result with the same time using the comparison algorithm.     

数字化工厂与虚拟制造的关系研究

为了区别数字化工厂和虚拟制造,研究了数字化工厂和虚拟制造的关系。基于PLM思想,给出数字化工厂的定义,并从广义和狭义角度分析数字化工厂的范畴和系统特点,与虚拟制造的概念和特点进行了对比分析。从功能集合角度分析了广义数字化工厂、虚拟制造和狭义数字化工厂的结构关系及相应系统的运行机理。在系统实施阶段,从关键技术、实施内容、侧重目标、实施特点等角度总结了三种生产组织方式的特点,给出了现有技术条件下的系统实施结论,研究了狭义数字化工厂的应用潜力。为信息时代制造业领域的后续研究提供了一定的方向性参考。     

Production planning and performance optimization of reconfigurable manufacturing systems using genetic algorithm

To stay competitive in the new dynamic market having large fluctuations in product demand, manufacturing companies must use systems that not only produce their goods with high productivity but also allow for rapid response to market changes. Reconfigurable manufacturing system (RMS) is a new paradigm that enables manufacturing systems to respond quickly and cost effectively to market demand. In other words, RMS is a system designed from the outset, for rapid changes in both hardware and software components, in order to quickly adjust its production capacity to fluctuations in market demand and adapt its functionality to new products. The effectiveness of an RMS depends on implementing its key characteristics and capabilities in the design as well as utilization stage. This paper focuses on the utilization stage of an RMS and introduces a methodology to effectively adjust scalable production capacities and the system functionalities to market demands. It is supposed that arrival orders of product families follow the Poisson distribution. The orders are lost if they are not met immediately. Considering these assumptions, a mixed integer nonlinear programming model is developed to determine optimum sequence of production tasks, corresponding configurations, and batch sizes. A genetic algorithm-based procedure is used to solve the model. The model is also applied to make decision on how to improve the performance of an RMS. Since there is no practical RMS, a numerical example is used to validate the results of the proposed model and its solution procedure.     

Production planning of a flexible manufacturing system in a material requirements planning environment

Early flexible manufacturing system (FMS) production planning models exhibited a variety of planning objectives; typically, these objectives were independent of the overall production environment. More recently, some researchers have proposed hierarchical production planning and scheduling models for FMS. In this article, we examine production planning of FMS in a material requirements planning (MRP) environment. We propose a hierarchical structure that integrates FMS production planning into a closed-loop MRP system. This structure gives rise to the FMS/MRP rough-cut capacity planning (FMRCP) problem, the FMS/MRP grouping and loading (FMGL) problem, and the FMS/MRP detailed scheduling problem.We examine the FMRCP and FMGL problems in detail and present mathematical programming models for each of these problems. In particular, the FMRCP problem is modeled as a generalized assignment problem (GAP), and a GAP-based heuristic procedure is defined for the problem. We define a two-phase heuristic for the FMGL problem and present computational experience with both heuristics. The FMRCP heuristic is shown to solve problems that exhibit a dependent-demand relation within the FMS and with FMS capacity utilization as high as 99 percent. The FMGL heuristic requires very little CPU time and obtains solutions to the test problems that are on average within 1.5 percent of a theoretical lower bound.This FMS/MRP production planning framework, together with the resulting models, constitutes an important step in the integration of FMS technology with MRP production planning. The hierarchical planning mechanism directly provides for system-level MRP planning priorities to induce appropriate production planning and control objectives on the FMS while simultaneously allowing for necessary feedback from the FMS. Moreover, by demonstrating the tractability of the FMRCP and FMGL problems, this research establishes the necessary groundwork upon which to explore systemwide issues pertaining to the coordination of the hierarchical structure.     

Applying case-based reasoning to manufacturing systems design

The object of this paper is to demonstrate the usefulness of case-based reasoning in manufacturing systems design, and to consider the characteristics of such a system. A CASE-based expert system called XBE (eXpert system By Examples) under development at Helsinki University of Technology is presented as an example. Two definitions (expert systems and CASE-based reasoning) are first explained before going into detail. The current understanding of the research group is presented. The main scope is technological, as opposed to applicative, i.e. case studies of applying CASE-based reasoning.     

An integrated planning approach for a nanodeposition manufacturing process

This paper deals with the planning problem in a nanodeposition manufacturing process, in which a toolbit that consists of a multilayer grid of micro/nanofluidic channels is used to deposit nanoscale liquid materials to desired positions on workparts to form solid patterns. The objective is to obtain a planning procedure that achieves efficient throughput for the studied nanodeposition manufacturing systems. We break down the studied problem into several sub-problems as design pattern decomposition, nanopore assignment, liquid material routing in the multilayer grid fluidic network, and toolbit path planning. Efficient algorithms are proposed to solve these sub-problems individually, and then finally integrated into a framework that systematically plans the nanodeposition manufacturing process. A software tool that plans, simulates, and controls the nanodeposition manufacturing process by implementing the proposed algorithms is reported in this paper.     

Improved responsiveness of reconfigurable manufacturing systems using a standards-based approach to assess manufacturing capacity

Market acceptance of the S95 enterprise-control system integration standard and its adoption in IEC 62264, combined with the use of the ISO 15745 application integration scheme, offers a common framework for integrating diagnostic and control activities with asset maintenance and management activities. This paper describes a standard-based approach to improve the responsiveness of reconfigurable systems by using condition-based maintenance and diagnostics information to assess manufacturing capacity. Use of integration models and interoperability schemas enable manufacturing management to have greater visibility into the current state and the capabilities of manufacturing assets to meet scheduled manufacturing requirements.     

分布式虚拟环境下的产品协同设计与制造

虚拟技术和计算机支持的协同工作（CSCW）技术已经渗透在设计与制造的活动中,并推动制造信息集成和网络协同设计与制造技术的发展。文中分析和讨论了分布式虚拟环境中的协同设计与制造系统的特点及其本要求,以五层结构形式给出了一处系统实现的框架模型。     

Resource-requirements planning in flexible manufacturing systems

In this paper, we address the problem of planning the requirements of some of the important resources in flexible manufacturing systems. Specifically, we model the problem of estimating the required numbers and types of machines and tools in the context of a cellular layout. A two-stage procedure is developed which first forms the part families, using the complete-linkage clustering method based on a new similarity index defined in terms of the tooling requirements, and then subsequently estimates the resource requirements to manufacture the part families using an integer programming model. Several variations of the model are discussed and a numerical example is given.     

A systematic approach for the sequence controller design in manufacturing systems

This paper presents a systematic approach for the design and implementation of the sequence controller in manufacturing systems. By employing the IDEF0, we construct the simplified Petri net controller (SPNC) through the material flow diagram and the information flow diagram. Then, the ladder logic diagram (LLD) can be transformed from the SPNC through the token passing logic (TPL). The proposed approach, including the IDEF0, SPNC, and TPL tools, leads to the standard IEC1131-3 LLD for PLC implementation. Finally, an application of a stamping process is provided to illustrate the design procedure of the developed approach .     

Object-oriented approach to the specification of manufacturing systems

This paper proposes an object-oriented approach to the specification of manufacturing systems. The specification model is built around a set of concurrent cooperating objects whose behaviour is described using communicating finite state machines. One of the interesting features of this approach is that the system's environment can be included in the model. This allows for rapid prototyping of the system through realistic simulations.     

The implementation of a cell-based manufacturing system

This paper describes the development of a cell-based manufacturing system. It considers all aspects of the implementation: the initial analysis of the problems of an existing system, product redesign for manufacture, cell design and cell implementation. The effectiveness of the resulting system is measured, using quantitative parameters. These include manufacturing lead times, due date performance and inventory levels. Other features, such as increased product quality, increased customer satisfaction and increased worker satisfaction, which cannot be measured easily, are discussed and shown to be major factors behind the successful implementation. Although presented as a case study the procedures adopted to facilitate the successful implementation are of general interest to any prospective manufacturing cell user.     

Methodological approach to planning and justifying technological innovation in manufacturing

The outline of a preliminary but general model of an innovation process, satisfying a number of previously defined specifications, is the aim of this paper. A model of the innovation process is first formulated, and the paper goes on to formulate the innovation design problem based on this model. Next, the main concepts for approaching the task of designing interventions for plant modification are outlined, and finally the problem of conditioning demands from customers is examined.     

A fuzzy-neural approach for estimating the monthly output of a semiconductor manufacturing factory

The customer order scheduling problem (COSP) is defined as to determine the sequence of tasks to satisfy the demand of customers who order several types of products produced on a single machine. A setup is required whenever a product type is launched. The objective of the scheduling problem is to minimize the average customer order flow time. Since the customer order scheduling problem is known to be strongly NP-hard, we solve it using four major metaheuristics and compare the performance of these heuristics, namely, simulated annealing, genetic algorithms, tabu search, and ant colony optimization. These are selected to represent various characteristics of metaheuristics: nature-inspired vs. artificially created, population-based vs. local search, etc. A set of problems is generated to compare the solution quality and computational efforts of these heuristics. Results of the experimentation show that tabu search and ant colony perform better for large problems whereas simulated annealing performs best in small-size problems. Some conclusions are also drawn on the interactions between various problem parameters and the performance of the heuristics.