Simulated annealing with auxiliary knowledge for process planning optimization in reconfigurable manufacturing

In this paper, three simulated annealing based algorithms that exploit auxiliary knowledge in different ways are devised and employed to handle a manufacturing process planning problem for reconfigurable manufacturing. These algorithms are configured based on a generic combination of the simulated annealing technique with; (a) heuristic knowledge, and (b) metaknowledge. Capabilities of the implemented algorithms are tested and their performances compared against a basic simulated annealing algorithm. Computational and optimization performances of the implemented algorithms are investigated and analyzed for two problem sizes. Each problem size consists of five different forms of a manufacturing process planning problem. The five forms are differentiated by five alternative objective functions. Experimental results show that the implemented simulated annealing algorithms are able to converge to good solutions in reasonable time. A computational analysis indicates that significant improvements towards a better optimal solution can be gained by implementing simulated annealing based algorithms that are supported by auxiliary knowledge.     

Industrial Additive Manufacturing: A manufacturing systems perspective

As Additive Manufacturing becomes increasingly prevalent in commercial manufacturing environments, the need to effectively consider optimal strategies for management is increased. At present most research has focused on individual machines, yet there is a wealth of evidence to suggest competitive manufacturing is best managed from a systems perspective. Through 14 case studies developed with four long-established Additive Manufacturing companies this paper explores the conduct of Industrial AM in contemporary manufacturing environments. A multitude of activities, mechanisms, and controls are identified through this detailed investigation of Additive Manufacturing operations. Based on these empirical results a general four component Industrial Additive Manufacturing System is developed, together with the identification of potential strategic opportunities to enhance future manufacturing.     

可重构制造系统的Petri网建模和分析方法

提出一种针对可重构制造系统的Petri网建模和分析方法．根据生产流程图可以得出制造系统的基本网模型,扩展基本网模型即可得到系统的Petri网模型．当生产任务发生改变并建立新的生产流程图时,可直接从原来的基本网模型构造出新构形的基本网模型．此外给出了系统重构代价的评价方法．仿真研究验证了该方法的有效性。     

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．     

Control architecture and design method of reconfigurable manufacturing systems

This paper proposes a control architecture for reconfigurable manufacturing systems and its design method based on Petri nets (Input Output Place Transition and Production Flow Schema), Service-Oriented Architecture and Holonic and Multi-Agent System techniques, among other good practices. The control architecture integrates value-added activities, information and resources. The method considers the exchange of knowledge among heterogeneous business workflow of manufacturing subsystems in different geographical locations, and allows modeling process, product, machine and device control. An example demonstrates advantages of the resulting control 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.     

Hierarchical production planning for complex manufacturing systems

A hierarchical approach to production planning for complex manufacturing systems is presented. A single facility comprising a number of work-centers that produce multiple part types is considered. The planning horizon includes a sequence of time periods, and the demand for all part types is assumed known. The production planning problem consists of minimizing the holding costs for all part types, as well as the work-in-process and the backlogging costs for the end items. We present a two-level hierarchy that is based on aggregating parts to part families, work-centers to manufacturing cells and time periods to aggregate time periods. The solution at the aggregate level is imposed as a constraint to the detailed level problems which are formulated for each manufacturing cell separately. This architecture uses a rolling horizon strategy to perform the production management function. We have employed perturbation analysis techniques to adjust certain parameters of the optimization problems at the detailed level to reach a near-optimal detailed production plan. Numerical results for several realistic example problems are presented and the solutions obtained from the hierarchical and monolithic approaches are compared. The results indicate that the hierarchical approach offers major advantages in computational efficiency, while the loss of optimality is acceptable.     

Configuration selection for reconfigurable control of piecewise affine systems

In this paper, the problem of configuration selection, i.e. sensor/actuator placement for piecewise affine (PWA) systems subject to both sensor and actuator faults is considered. A method is proposed that provides a tool for the design phase to decide about the optimal placement of sensor/actuators where the reconfigurability of the system subject to sensor and actuator faults is also taken into account. Using a lattice of possible configurations (sensor/actuator placements), the reconfigurability of the system subject to faults for each configuration is evaluated and based on that one can draw conclusions about the reconfigurability of the system and the optimal configuration in the architecture design phase. A reconfigurable control must ensure stability of the reconfigured system and, if possible, a graceful degradation in the performance. Therefore, in the proposed reconfigurability analysis, we consider both stabilisability and performance of the system. The efficiency of the proposed method is demonstrated in several numerical examples.     

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

The current market's demand for customization and responsiveness is a major challenge for producing intelligent, adaptive manufacturing systems. The Multi-Agent System (MAS) paradigm offers an alternative way to design this kind of system based on decentralized control using distributed, autonomous agents, thus replacing the traditional centralized control approach. The MAS solutions provide modularity, flexibility and robustness, thus addressing the responsiveness property, but usually do not consider true adaptation and re-configuration. Understanding how, in nature, complex things are performed in a simple and effective way allows us to mimic nature's insights and develop powerful adaptive systems that able to evolve, thus dealing with the current challenges imposed on manufacturing systems. The paper provides an overview of some of the principles found in nature and biology and analyses the effectiveness of bio-inspired methods, which are used to enhance multi-agent systems to solve complex engineering problems, especially in the manufacturing field. An industrial automation case study is used to illustrate a bio-inspired method based on potential fields to dynamically route pallets.     

Technical investment planning of flexible manufacturing systems—The application of practice-oriented methods

Flexible manufacturing systems (FMS) exhibit a high degree of automation of the machining system and of the workpiece, and for the information flow systems. Therefore, these systems are amongst the most complex production installations and their technical investment planning must be undertaken with great care.This paper introduces a strategic planning procedure and describes auxiliary aids for the selection of the components and for structuring of the overall system. Computer programs for the selection of machine tools and for the simulation of the manufacturing process sequence are part of this procedure. The application of the methods is illustrated by means of several problem situations arising from industrial production companies; the examples show the practical usefulness of the developed auxiliary techniques. The planning accuracy possible by these methods reduces the investment risk associated with the use of these complex manufacturing systems.Also described is an integrated system for the technical investment planning of flexible manufacturing systems which comprises both existing methods and new auxiliary means for planning the machining systems and the technical/organizational overall concept.     

Neural networks implementation for modeling and control design of manufacturing systems

This paper presents a dynamic neural network implementation for the modeling and control design of a class of manufacturing systems. The evolution of the considered systems is supposed to be continuous and non-stochastic. A separate implementation of the system elements is detailed. These elements are then connected together in order to obtain a global net that simulates the behavior of the real system. The obtained model is modular and can be adapted easily for any modification of the system. Permanent correction rules are developed to control the speed of the machines according to a desired profile and to take into consideration the buffers limited capacities. The convergence of the control design is proved. The proposed approach is applied on an exhaust valves assembly workshop.     

Applications of queueing structures in manufacturing systems

This survey paper discusses and, to some extent, identifies manufacturing sub-systems that can be represented using accepted queueing models. Aggregate performance measures can be obtained through application of these models. Depending on the complexity of the congestion characteristics of the system, the standard results from queueing theory texts may yield guidelines for selection of optimal operational parameters.     

Performance evaluation for manufacturing systems under control-limit maintenance policy

Maintenance decision-making in large manufacturing systems is complex as it requires the integration of various information. A control-limit policy is popular in practice, where maintenance is carried out when the degradation state of a machine reaches a threshold value. In this paper, by developing a framework based on discrete-time Markov chain models, we evaluate the system performance under the control-limit policy, in manufacturing systems that consist of multi-state machines and intermediate buffers. An exact analysis is performed for a two-machine-one-buffer system and an approximation method based on system decomposition is developed for multi-stage systems. Both steady-state and transient performance is analyzed. Numerical examples are presented to demonstrate the accuracy of the proposed method and the impact of different parameters (e.g., buffer capacity, uncertainty in the maintenance duration) on the system performance.     

Scalability limits of Bag-of-Tasks applications running on hierarchical platforms

Bag-of-Tasks applications are parallel applications composed of independent (i.e., embarrassingly parallel) tasks, which do not communicate with each other, may depend upon one or more input files, and can be executed in any order. Each file may be input for more than one task. Examples of Bag-of-Tasks (BoT) applications include Monte Carlo simulations, massive searches (such as key breaking), image manipulation applications and data mining algorithms. A common framework to execute BoT applications is the master-slave topology, in which the user machine is used to control the execution of tasks. In this scenario, a large number of concurrent tasks competing for resources (e.g., CPU and communication links) severely limits application execution scalability. This paper is devoted to study the scalability of BoT applications running on multi-node systems (such as clusters and multi-clusters) organized as hierarchical platforms, considering several communication paradigms. Our study employs a set of experiments that involves the simulation of various large-scale platforms. The results presented provide important guidelines for improving the scalability of practical applications.     

Computer aids to the design of integrated manufacturing systems

Building an Integrated Manufacturing System is a complicated and expensive task. There are very few companies anywhere that will deliver turn-key CAD/CAM systems, far less produce a full line of hardware and software products covering every function required. In designing such a system we are faced with the problem of the proper interfacing and coordination of several hundreds of functional sub-systems. It is, therefore, a natural endeavour to use CAD methods in the design of CAD/CAM systems. Brief outlines are given of a highly interactive system having formalized diagrams and alphanumeric information on the input side, and readable system documentation and analysis reports, on the output side - both interacting to widely accepted extant techniques. The structure of a more complex system affording further facilities is also presented.     

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.     

A model for assessing the layout structural complexity of manufacturing systems

The layout of a manufacturing facility/system not only shapes its material flow pattern and influence transportation and operation cost, but also affects logistics and parts/machine assignment decisions. The layout of manufacturing systems determines its structural complexity by virtue of its design configuration characteristics. This paper introduces a new model and indices for assessing the structural complexity of manufacturing systems layout in the physical domain. Six complexity indices, based on the physical structural characteristics of the layout, have been introduced and formulated. They are layout density, path, cycle, decision points, redundancy distribution and magnitude indices. An overall Layout Complexity Index (LCI) which combines all indices is developed using a novel method based on radar plots which is insensitive to the order of plotting the individual indices. The use of the developed LCI is demonstrated using six typical types of manufacturing systems layouts and relevant guidelines are presented. The developed model and complexity indices help design system layouts for least complexity and compare layout alternatives that meet the specifications, at early design stages. It supports making trade-off decisions regarding manufacturing systems flexibility and complexity and their associated costs.     

Designing Holonic manufacturing systems

This paper discusses the design of Holonic manufacturing systems (HMS), with emphasis on manufacturing control. First, it discusses the concept of a Holonic system. Second, it presents the HMS reference architecture for manufacturing control. Third, it addresses the overall design problem, i.e. designing both the holonic control system and the underlying manufacturing system. Finally, the paper addresses the design and development of the control software itself.     

Smooth time-optimal tool trajectory generation for CNC manufacturing systems

An optimization approach is proposed in this paper for generating smooth and time-optimal path constrained tool trajectory for Cartesian computer numerical control (CNC) manufacturing systems. The desired smooth time-optimal trajectory generation (STOTG) problem is formulated as a general optimal control problem. And axis jerk (derivative of acceleration with respect to time) constraints are introduced into this problem to remove discontinuities of the acceleration profiles. The desired smoothness of the trajectory can be accomplished by adjusting the values of jerk constraints. A control vector parameterization (CVP) method is applied to convert the optimal control problem into a nonlinear programming (NLP) problem which can be solved conveniently and effectively. The third derivative of the path parameter with respect to time (pseudo-jerk) and jerk act as optimization variables. The pseudo-jerk is approximated as piecewise constant, thus for at least second-order continuous parametric path, the resulted optimized trajectory with respect to time is also at least second-order continuous. Sequential quadratic programming (SQP) method is used to solve the NLP problem, through which numerical solution is obtained. Non-smooth (i.e. without considering jerk constraints) time-optimal trajectory generation (non-STOTG) problem is also considered in this paper for the purpose of comparison. Solutions of time-optimal trajectory generation (TOTG) problems for two test paths are performed to verify the effectiveness of the proposed approach.