A multi-agent based agile manufacturing planning and control system

In today’s manufacturing enterprise, the performance of customer service level (e.g., short ordering-to-delivery time, low price) is highly dependent on the effectiveness of its manufacturing planning and control system (MPCS). However, most of the current MPCS, employed the hierarchical planning approach, may have some drawbacks, such as structural rigidity, difficulty of designing a control system, and lack of flexibility. Currently, RFID (Radio Frequency Identification) technology has been applied to enhance the visibility, accountability, track ability and traceability of manufacturing system whenever the accurate and detailed manufacturing information (e.g., raw material, WIP, products in factory and products in the down streams) of products will be followed in real-time basis by RFID technique. In addition, a multi-agent approach may be applied in a distributed and autonomous system which allows negotiation-based decision making. Therefore, the objective of this research is to study the application of RFID technique and multi-agent system (MAS) in developing an agent-based agile manufacturing planning and control system (AMPCS) to respond to the dynamically changing manufacturing activities and exceptions.In AMPCS, RFID-based manufacturing control (R-MC) module plays the role of controlling the manufacturing system in which production items and manufacturing resources attached with RFID tag may actively feedback production status to and receive production and operations schedule from advanced manufacturing planning (AMP) module. In addition, a bidding process and algorithm is developed to generate operations schedule by using the characteristics of MAS. Performance analysis (PA) module is responsible not only for evaluating the scheduling results but also for evaluating the performance of production execution. The development of an AMPCS for an automated manufacturing cell demonstrates that the integration of RFID technique and MAS in developing an agile manufacturing planning and control system can really possess the characteristics of visibility, accountability, track ability, responsiveness, and flexibility in a distributed and dynamic manufacturing system.     

Shop floor control using the tactical ratio and monitoring system

In the fall of 1979, a decision was made by a manufacturing group steering committee to develop a system of shop floor control that recognized the reality of doing business in a practical rather than a theoretical way.A system was required that was capable of handling the management of work-in-process lots—as one group executive vice-president put it—“in the trenches”.Typical problems had to be dealt with in the system, such as additions, cancellations, pull ups, push outs, customer emergencies, delivery dates, short lead times, etc.The initial approach was to investigate the many software packages available on the market. A team of three manufacturing and data processing representatives was formed to undertake the search. After months of analysis and reviews, the conclusion was reached that a commercial system was not available to deal with the myriad of problems encountered everyday in shop floor control. As a result, the decision was made to develop an in-house system.     

Capacity and flexibility planning of an economical manufacturing system

This paper presents a simple dynamic model for determining the capacity and the flexibility of a manufacturing system over a finite planning horizon. We consider a problem that arises from the development phase of an investment plan for an economical manufacturing system. The objective is to minimize the total cost associated with the capacity expansion, flexibility expansion and operation. This problem is formulated as an integer program. A Lagrangian heuristic is developed for determining a near optimal solution to this integer program. Finally, we show how to incorporate aggregate production planning into the model.Based on a presentation given at the ORSA/TIMS Miami meeting in 1986.     

Adaptive genetic algorithm for advanced planning in manufacturing supply chain

A main function for supporting global objectives in a manufacturing supply chain is planning and scheduling. This is considered such an important function because it is involved in the assignment of factory resources to production tasks. In this paper, an advanced planning model that simultaneously decides process plans and schedules was proposed for the manufacturing supply chain (MSC). The model was formulated with mixed integer programming, which considered alternative resources and sequences, a sequence-dependent setup and transportation times.The objective of the model was to analyze alternative resources and sequences to determine the schedules and operation sequences that minimize makespan. A new adaptive genetic algorithm approach was developed to solve the model. Numerical experiments were carried out to demonstrate the efficiency of the developed approach. Received: June 2005 / Accepted: December 2005     

vMES: Virtualization aware manufacturing execution system

The large scale emergence in the last decade of various cloud solutions, ranging from software-as-a-service (SaaS) based solutions for business process management and implementation to very sophisticated private cloud solutions capable of high performance computing (HPC) and efficient virtualization, constitute the building blocks for engineering the next generation of flexible enterprise systems that can respond with great agility to changes in their environment. These new technologies are adopted at a certain level by manufacturing enterprises in order to advance in a new era of mass customization where flexibility, scalability and agility are the differentiating factors. In this context, this paper introduces the virtualized manufacturing execution system (vMES), an intermediate layer in the manufacturing stack, and discusses the advantages and limitations offered by this approach for manufacturing enterprises. A classification of MES workloads based on the ISA-95 function model is presented, focusing on the virtualization techniques suitable for each workload, considering the algorithms and technologies used and the virtualization overhead. A pilot vMES implementation using a parallel process for smart resource provisioning and automatic scaling is also presented. The pilot implementation using six Adept robots and one IBM CloudBurst 2.1 private cloud and an ISA-95 based MES is described; the virtualization sequence is analyzed in several scenarios of resource workload collocation on physical cloud blades with and without perturbations.     

A fuzzy hierarchical reinforcement learning based scheduling method for semiconductor wafer manufacturing systems

Scheduling semiconductor wafer manufacturing systems has been viewed as one of the most challenging optimization problems owing to the complicated constraints, and dynamic system environment. This paper proposes a fuzzy hierarchical reinforcement learning (FHRL) approach to schedule a SWFS, which controls the cycle time (CT) of each wafer lot to improve on-time delivery by adjusting the priority of each wafer lot. To cope with the layer correlation and wafer correlation of CT due to the re-entrant process constraint, a hierarchical model is presented with a recurrent reinforcement learning (RL) unit in each layer to control the corresponding sub-CT of each integrated circuit layer. In each RL unit, a fuzzy reward calculator is designed to reduce the impact of uncertainty of expected finishing time caused by the rematching of a lot to a delivery batch. The results demonstrate that the mean deviation (MD) between the actual and expected completion time of wafer lots under the scheduling of the FHRL approach is only about 30 % of the compared methods in the whole SWFS.     

A distributed scheduling and shop floor control method

We suggest a market-like framework for scheduling and shop floor control in computer-controlled manufacturing systems where each resource agent and part agent acts like an independent profit maker. A part-resource negotiation procedure is suggested including price-based bid construction and price revising mechanism. Alternative routings for each production order are considered in scheduling and shop floor control. A simulation-based scheduling method is suggested to estimate the start time and the completion time of each task. We develop a prototype soffivare which utilizes the object-oriented concept.     

An object-oriented manufacturing control system

This paper presents the development of an event-driven control architecture and its implementation in a physical simulator of a computerized manufacturing system using object-oriented techniques. The architecture was developed to improve the efficiency of handling concurrent control events in the DOS environment. In the implementation, the control system of the physical simulator consists of four distinct layers of control devices: a PC/386 computer, a microcontroller, I/O modules and the system's control devices such as motors, solenoids and sensors. A control program residing in the PC/386 coordinates system-level tasks such as event scheduling, while a BASIC program running on the microcontroller handles all low-level control tasks such as sensor monitoring and motion control. The concepts and developments presented in this paper should help in implementing an efficient control system for both CIM systems and their physical simulators.     

Development of a new dioid algebraic model for manufacturing with the scheduling decision making capability

The dioid algebraic model, which is developed in this paper, captures the discontinuous nature of Discrete-Event Dynamic Systems and has widespread applicational capabilities. As a further improvement over existing dioid algebraic models, decision making capability is introduced to the developed dioid algebraic model. With this new capability, sequencing decisions at each machine can be represented in the model. Furthermore, the developed algebraic model is capable of representing job and resource unavailability, technological constraints, alternative process plans, and is easily modifiable to include new jobs and exclude finished jobs. In a possible application, the model can be used in representing dynamic scheduling problems and can be used as an important part of a real-time control and scheduling scheme of a manufacturing system.     

Application of a continuous supervisory fuzzy control on a discrete scheduling of manufacturing systems

This paper considers the design and the practical implementation of a stable multiple objective real-time scheduling problem for a complex production system. In this paper, a complex production system is viewed as a kind of systems producing a variety of products (multiple-part-type) under constraints and multiple production objectives often conflicting. Previously, fuzzy control theory and fuzzy intervals arithmetic have been used to develop a distributed and supervised continuous-flow control architecture. In this framework, the objective of the distributed control structure is to balance the production process by adjusting the continuous production rates of the machines on the basis of the average local behavior. The supervisory control methodology aims at maintaining the overall performances within acceptable limits. In the new proposed approach, the problem of a stable real-time scheduling of jobs is considered at the shop-floor level. In this context, as the stability of the control structure is ensured, the actual dispatching times are determined from the continuous production rates through a discretization procedure. To deal with conflicts between jobs at a shared machine, a decision is made. It concerns the actual part to be processed and uses some criterions representing a measure of the job's priority. The simulation results show the validity of the proposed approach in terms of production cost, robustness and system stability.     

The effect of system configuration and ramp-up time on manufacturing system acquisition under uncertain demand

The objective of this paper is to investigate the optimal allocation of capacity investments at the tactical decision-making level by incorporating the configuration characteristics of selected system alternatives comprising Dedicated Manufacturing Systems (DMS) and Reconfigurable Manufacturing Systems (RMS). Particularly, sequencing of stages in a series or a parallel configuration impacts the responsiveness in addressing capacity change requirements. We analyze what type of configuration is more suitable for a manufacturer in terms of service level and cost. We propose a mixed integer programming model by incorporating various ramp-up time patterns, which define system scalability lead time. By solving the MIP model to optimality, we aim to see how capacity is allocated to RMS and DMS based on system cost, system responsiveness, and reconfiguration speed. A discrete event simulation model is used to validate the MIP results under uncertain demand scenarios.     

A scheduling decision aid in glass fiber manufacturing

A decision aid for scheduling production in glass fiber manufacturing industry is described. The methodology combines a linear programming (LP) optimization model with a heuristic model. The LP model determines production goals; the heuristic model then uses the LP output to incorporate system-specific constraints in developing processing sequences.     

Method for analysis and dynamism of factory structure in automotive manufacturing

A turbulent environment characterized by unsteady economic cycles, customized products, a growing bandwidth of products, an exploding number of variants and shorter product life cycles force manufacturers to permanent adaptation of their factories. Flexible and changeable structures will be required to enable factories dealing with the technological challenges and economic pressure of the future competitively. In order to achieve changeability objectives in manufacturing, a detailed analysis of existing structures and its representative attributes is essential. It is the basis for systematic structure planning of factories. In this paper a method for analyzing the capacitive and technological structure of a factory embedded in a network of manufacturing and its network of suppliers is presented. The synchronization of product and production development under the influence of change is intended. Therefore, the structural views of product and production are specifically in focus of the method. Based on the results of the analysis models an approach of a tool for giving product and production structure dynamism is suggested to investigate the effects and dependencies of change drivers in manufacturing.     

A part-machine assignment algorithm for cellular manufacturing with machine capacity constraints

Many researchers have attempted to solve the cellular manufacturing problem using various clustering techniques; however, few have considered the effect of production constraints. In this paper an algorithm for the assignment of parts to machines to solve the group technology problem which takes into consideration the effect of machine capacity constraints is discussed. The effect of this constraint is demonstrated by an example.     

Optimal cycle production of a manufacturing system subject to deterioration

A single part type, single machine, fluid model manufacturing system is considered. The machine is subject to a deterministic deterioration process, which depends on the operation rate. The objective is to minimize a long term average cost index which penalizes inventory surplus and backlog. The optimal policy determined presents some similarities with the policy conjectured optimal in the past for a similar Markovian formulation. The considered problem can be applied to several real contexts, and not just from the manufacturing domain, as briefly discussed in the paper.     

基于多Agent的可重构制造系统集成模型

应用控制、管理和维护一体化的自动化技术,建立了基于多Agent的可重构制造系统RMS（Reconfigurable Manufacturing System）集成模型。该模型集成了基于多Agent 的RMS重构模型、控制模型和故障诊断模型,将RMS的控制、管理和维护联系起来,并给出了该模型的UML（Unified Modeling Langurage）活动图,最后举例验证了模型的可行性。     

A decision analysis based system for formulating manufacturing strategy

Although a substantial number of decision and management science models of production management decisions have been developed, these models have not generally addressed the strategic framework of manufacturing, considered as an integrated pattern of decisions. They have usually been concerned with only one aspect of manufacturing strategy such as capacity or technology choice and have framed that choice using a single dimension of value such as cost. This study develops a comprehensive decision analysis model base which can be implemented as a DSS, to gain insight about the broader manufacturing strategy set. Decision trees, influence diagrams, Monte Carlo risk analysis and multiple criteria utility functions can contribute to a better understanding of and to decision support for manufacturing strategy formulation.     

Feeding sequence selection in a manufacturing cell with four parallel machines

This paper deals with the problem of finding the optimum feeding sequence in manufacturing cells with machines fed by robots. The particular real case of a cell with four parallel identical machines working alternately on two pallets each one, fed by one robot and with random assistance requirements, is introduced and analyzed. The cell has been modelled and simulation results for different feeding sequences are presented. A general discriminant function to select the best feeding sequence between a fixed and a variable sequence was determined using simulation results for different working and loading times and pattern recognition techniques.     

Machine planning for manufacturing: dynamic resource allocation and on-line supervisory control

In this paper*, we provide tools for integrating machine planning and manufacturing. Specifically, we show how assembly trees can be coded into operators for machine planners and how machine planners can represent flow-lines, assembly and job-shop choices. We provide a polynomial-time algorithm for succinctly combining multiple plans; the resulting plan can be expressed as four matrices that are equivalent to a Petri net. We also provide a dynamic supervisory controller that can execute a single plan or switch between multiple plans as real-time conditions change.     

支持快速扩散制造的制造执行系统研究

结合武器装备快速变批量生产的需求,对武器装备快速扩散制造的概念和支撑理论进行了介绍;针对快速扩散制造过程中若干核心问题,提出了支持快速扩散制造的制造执行系统。介绍了制造执行系统实施的三个关键技术:支持快速扩散制造的生产计划与动态调度技术;基于资源平台的物料全生命周期管理及应用集成技术;基于工作流的制造过程自动导航与驱动技术。最后对制造执行系统的总体体系结构和功能模型展开探讨和研究。该系统在航天制造企业应用的效果显著,证明了该系统整体方案的可行性和有效性。