Ergodicity of hedging control policies in single-partmultiple-state manufacturing systems

The Markov renewal viewpoint of single-part/multiple-state manufacturing systems under hedging control policies, subjected to a constant rate of demand for parts, is used to derive sufficient criteria to guarantee the ergodicity of the resulting parts surplus process. The criteria are simple and directly verifiable from an analysis of the Markov chain characterizing the dynamics of the discrete manufacturing system production state. A key intermediate result in reaching these criteria is a potentially very useful system of linear differential equations with boundary conditions which can be generalized to permit computation of moments of arbitrary order for sojourn times in the regions between successive hedging points in the parts surplus space     

Optimality of hedging point policies in the production control offailure prone manufacturing systems

We study the necessary and sufficient conditions for the optimality of the hedging point policy for production systems in which the failure rate of machines depends on the rate of production. We focus on a one machine one part-type and infinite horizon discounted cost problem. It is shown that when the failure rate is independent of the rate of production and a constant, the hedging point policy is provably optimal. The main result of this paper is to show that the linearity of the failure rate function is both necessary and sufficient for the optimality of the hedging point policy     

Optimal hedging point control for a failure-prone manufacturing system

This paper considers a manufacturing system with multiple operational modes producing one part type. The part processing time at each operational mode is exponentially distributed and its rate is controllable. The demand arrival is random and described by a Poisson process. By minimizing an infinite-horizon discounted expected cost function, the optimal service rate control is derived. It is proved that the optimal policy is of a hedging point structure by examining the properties of the optimal cost function such as convexity, monotonicity and asymptotic behaviours. The hedging points at different operational modes can be ordered according to their production capacities. The relationships of the hedging points with some system parameters are presented. These structural properties of the optimal control policy are helpful in finding simple and realistic suboptimal policies for practical manufacturing systems. A numerical example is given to demonstrate our results.     

A stochastic hybrid state model for optimizing hedging policies in manufacturing systems with randomly occurring defects

The paper addresses the optimal production control problems for an unreliable manufacturing system that produces items that can be regarded as conforming or nonconforming. A new stochastic hybrid state Markovian model with three discrete states, also called modes is introduced. The first two, operational sound and operational defective are not directly observable, while the third mode, failure, is observable. Production of defective parts is respectively initiated and stopped at the random entrance times to and departure times from the defective operational mode. The intricate, piecewise-deterministic dynamics of the model are studied, and the associated Kolmogorov equations are developed under the suboptimal class of hedging policies. The behavior of the model is numerically investigated, optimized under hedging policies, and subsequently compared to that of a tractable extension of the two-mode Bielecki-Kumar single machine model, where both conforming and defective parts are simultaneously produced in the operational mode, while the ratio of produced non conforming to conforming parts remains fixed.     

Semiconductor manufacturing process control and monitoring: A fab-wide framework

The semiconductor industry has started the technology transition from 200 mm to 300 mm wafers to improve manufacturing efficiency and reduce manufacturing cost. These technological changes present a unique opportunity to optimally design the process control systems for the next generation fabs. In this paper we first propose a hierarchical fab-wide control framework with the integration of 300 mm equipment and metrology tools and highly automated material handling system. Relevant existing run-to-run technology is reviewed and analyzed in the fab-wide control context. Process and metrology data monitoring are discussed with an example. Missing components are pointed out as opportunities for future research and development. Concluding remarks are given at the end of the paper.     

半Markov 控制过程在折扣代价准则下的最优平稳策略

讨论一类半Markov控制过程(SMCP)的折扣代价性能优化问题．通过引入一个矩阵，该矩阵可作为一个Markov过程的无穷小矩阵，对一个SMCP定义了折扣Poisson方程，并由这个方程定义了α-势．基于α-势，给出了由最优平稳策略所满足的最优性方程．最后给出一个求解最优平稳策略的迭代算法，并提供一个数值例子以表明该算法的应用．     

Design for manufacturing meets advanced process control: A survey

Nanometer IC designs are increasingly challenged to achieve manufacturing closure, i.e., being fabricated with high product yield due to feature miniaturizations and process variations. Realizing the critical importance of addressing manufacturability/yield during design (which is loosely termed as DFM, design for manufacturing), there has been a surge of research activities recently from both academia and industry under the “DFM” umbrella. While the primary goal of DFM is to enlarge the manufacturing process yield window, DFM needs to work together with advanced process control (APC) to meet such window, which may be shrinking and changing from design to design. The paper will survey the key DFM activities and discuss related advanced process control issues (i.e., the counterpart of manufacturing for design) to provide a holistic perspective on the design and process integration.     

Petri net based process scheduling: A model of the control system of flexible manufacturing systems

In this paper, we propose a class of algorithms for the sub-optimal solution of a particular class of problems of process scheduling, particularly focusing on a case study in the area of flexible manufacturing systems (FMSs). The general class of problems we face in our approach is characterized as follows: there is a set of concurrent processes, each formed by a number of temporally related tasks (segments). Tasks are executable by alternate resource sets, different both in performance and costs. Processes and tasks are characterized by release times, due dates, and deadlines. Time constraints are also present in the availability of each resource in resource sets. It has been proven that such a problem does not admit an algorithm for an optimal solution in polynomial time. Our proposed algorithm finds a sub-optimal schedule according to a set of optimization criteria, based on task and process times (earliness, tardiness), and/or time independent costs of resources. Our approach to process scheduling is based on Timed Coloured Petri Nets. We describe the structure of the coordination and scheduling algorithms, concentrating on (i) the general-purpose component, and (ii) the application-dependent component. In particular, the paper focuses on the following issues: (i) theautomatic synthesis of Petri net models of the coordination subsystem, starting from the problem knowledge base; (ii) the dynamic behavior of the coordination subsystem, whose kernel is a High Level Petri net executor, a coordination process based on an original, general purpose algorithm; (iii) the structure of the real-time scheduling subsystem, based on particular heuristic sub-optimal multi-criteria algorithms. Furthermore, the paper defines the interaction mechanisms between the coordination and scheduling subsystems. Our approach clearly distinguishes the mechanism of the net execution from the decision support system. Two conceptually distinct levels, which correspond to two different, interacting implementation modules in the prototype CASE tool, have been defined: theexecutor and thescheduler levels. One of the outstanding differences between these levels is that the executor is conceived as a fast, efficient coordination process, without special-purpose problem-solving capabilities in case of conflicts. The scheduler, on the other hand, is the adaptive, distributed component, whose behavior may heavily depend on the problem class. If the scheduler fails, the executor is, in any case, able to proceed with a general-purpose conflict resolution strategy. Experimental results on the real-time performance of the kernel of the implemented system are finally shown in the paper. The approach described in this paper is at the basis of a joint project with industrial partners for the development of a CASE tool for the simulation of blast furnaces.     

Optimal control of production rate in a failure prone manufacturing system

We address the problem of controlling the production rate of a failure prone manufacturing system so as to minimize the discounted inventory, cost, where certain cost rates are specified for both positive and negative inventories, and there is a constant demand rate for the commodity produced. The underlying theoretical problem is the optimal control of a continuous-time system with jump Markov disturbances, with an infinite horizon discounted cost criterion. We use two complementary approaches. First, proceeding informally, and using a combination of stochastic coupling, linear system arguments, stable and unstable eigenspaces, renewal theory, parametric optimization, etc., we arrive at a conjecture for the optimal policy. Then we address the previously ignored mathematical difficulties associated with differential equations with discontinuous right-hand sides, singularity of the optimal control problem, smoothness, and validity of the dynamic programming equation, etc., to give a rigorous proof of optimality of the conjectured policy. It is hoped that both approaches will find uses in other such problems also. We obtain the complete solution and show that the optimal solution is simply characterized by a certain critical number, which we call the optimal inventory level. If the current inventory level exceeds the optimal, one should not produce at all; if less, one should produce at the maximum rate; while if exactly equal, one should produce exactly enough to meet demand. We also give a simple explicit formula for the optimal inventory level.     

Development of an internet and fuzzy based control system of manufacturing process

The aim of this work is to develop an Internet and fuzzy based control and data acquisition system for an industrial process plant which can ensure remote running and fuzzy control of a cement factory. Cases studies of the proposed system application in three cement factories in Algeria, SCAEK (Setif), SCIMAT (Batna), and SCT (Tebessa), are discussed. The remote process control consists of alarms generated during running of the processes while maintaining and synchronizing different regulation loops thus ensuring automatic running of processes smoothly. In addition, fuzzy control of the kiln and the other two mills ensures that the system is operational at all times with minimal downtime. The process control system contains different operator station (OP), alarms table and a provision to monitor trends analysis. The operator can execute any operation according to his authorised access assigned by the system administrator using user administration tool. The Internet technology is used for human security by avoiding all times presence of operators at site for maintenance. Further, in case of a breakdown, the problem would be remotely diagnosed and resolved avoiding requirement of an expert on site thus eliminating traveling cost, security risks, visa formalities, etc. These trips are difficult to organize (costs, visas, risks). So the enterprise can reduce downtimes and travel costs. In order to realize a process control system guided by operators in the main control room or through Internet, the process control is based on programming in PCS 7 utilizing Cemat library and Fuzzy Control++ Siemens tools.     

自动制造系统的稳健控制方法的综述

随着科学技术的快速发展,制造自动化在制造工厂已经成为一个主流方向.在过去的几十年中,研究人员已经对自动制造系统的死锁问题做了大量的研究.但是大多数解决方案总是假设分配的资源不会故障.然而,任何一个制造研究者都知道,资源故障来自各种各样的原因,包括工件破损、传感器故障、零件缺失和电器失灵等.显然,一旦资源发生故障,后续加工路径中需要使用这个故障资源的进程将停滞,不能完成其加工生产,直到故障资源被修复.那些不使用故障资源的支路也会被发生停滞的进程所阻塞.最坏的情况就是一个简单的资源故障可能会导致整个系统的崩溃.因此,制造系统中的资源故障问题急需解决.通过分析大量的文献资料,本文对解决死锁和阻塞问题的控制方法做了系统的总结研究.同时,对本文提出的稳健无死锁控制策略以及亟待开展的研究工作做了详细的介绍.     

A general hybrid semi-parametric process control framework

A general hybrid semi-parametric process control framework is proposed in this study. The motivation was the integration of different levels of knowledge systems into a general hybrid semi-parametric control structure, of which the general linear controller or the PID controller are, for instance, particular cases.Several hybrid semi-parametric control structure variants and tuning methods are benchmarked in relation to a simulated bioprocess control problem, namely closed-loop control of the biomass concentration through manipulation of the substrate feeding rate, coupled with the closed-loop control of the dissolved oxygen concentration through the stirring velocity. The results demonstrate that (i) due to the hybrid approach the control loop can be closed without any additional identification experiments; (ii) the incorporation of different types of knowledge can enhance the controller performance, when compared to structures without a priori knowledge; (iii) knowledge incorporation seems to facilitate the tuning of the controller; and (iv) the control action can be analyzed in relation to structural information incorporated into the hybrid controller.     

Practical simulation application: Evaluation of process control parameters in Twisted-Pair Cables manufacturing system

Intensive competition and rapid technology development of Twisted-Pair Cables (TPC) industry have left no room for competing manufacturers to harbour system inefficiencies. TPC are used in various communication and networks hardware applications; their manufacturing facilities face many challenges including various product configurations with different equipment settings, different product flows and Work in Process (WIP) space limitations. The quest for internal efficiency and external effectiveness forces companies to align their internal settings and resources with external requirements/orders, or in different words, significant factors must be set appropriately and identified prior to manufacturing processes. Integrated definition models (IDEF0, IDEF3) in conjunction with a simulation model and a design of experiments (DOE) have been developed to characterize the TPC production system, identify the significant process parameters and examine various production setting scenarios aiming to get the best product flow time.     

A general stability criterion for congestion control with diverse communication delays

A unified duality model is proposed for describing the current Internet congestion control algorithms. Based on this model, the problem of the local asymptotic stability of the congestion control with heterogeneous propagation delays is formulated and solved. A general stability criterion is proved by using the stability theory for quasi-polynomials.     

Stochastic manufacturing system with process deterioration and machine breakdown

This paper presents a realistic manufacturing inventory model with process deterioration and machine breakdown. In economic manufacturing quantity model, process usually starts with ‘in-control’ state and produces items of good quality. After some random point of time, process may deteriorate and shift to ‘out-of-control’ state due to occurrence of assignable cause. From that point, process produces some percentage of non-conforming items. Further process deterioration after machine shift may result in machine breakdown at any random time during the production period. If machine breakdown occurs during the production period, then corrective (emergency) repair is performed immediately otherwise preventive (regular) repair is performed at the end of production period. The proposed model is formulated assuming that the time required for production facility shifting from ‘in-control’ state to ‘out-of-control’ state, time when machine breaks down, corrective and preventive repairing time and demand of items follows probability distribution. We have derived analytically the optimal production time which minimises the total expected production cost annually for machine breakdown and no machine breakdown cases. The solution procedure is illustrated with the help of numerical examples for different probability distributions. Sensitivity of the optimal solution with respect to different parameters are also analysed.     

Synthesis of control policies for manufacturing systems using the control canonical form

In this paper, multivariable systems theory is used to synthesize control policies for a manufacturing system which is modelled as a linear discrete-time multivariable dynamical system. The state variables of the system are the rates-of-flow of parts at the various work stations, the buffer inventories, anil the finished product inventories. The control inputs are the man-hours per week required for the various processes involved in the manufacturing system, anil the disturbance inputs are the demands for semi-finished and finished parts. The behaviour of the controlled manufacturing system is illustrated by the presentation of the results of computer simulation studies showing typical transient and steady-state response characteristics,     

A general analysis and control framework for process systems with inventory recycling

In this work, we generalize our previous results concerning the impact of material recycling and energy recovery on plant dynamics and control. We define a generic class of integrated process systems, in which an extensive quantity that obeys conservation laws is recovered from the process output and recycled to the process feed; the operation of the system is assumed to be subject to time‐varying, measurable disturbances. We establish, in this general case, that integration is conducive to the emergence of a two‐time‐scale dynamic behavior and derive reduced‐order models for the dynamics in each time scale. Subsequently, we postulate a hierarchical control framework that exploits these dynamics results in the design of coordinated fast and slow feedback/feedforward controllers and formulate a stability result for the closed‐loop system. We demonstrate these concepts on a case study concerning an energy‐integrated process. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

A decision support system for material and manufacturing process selection

The material and manufacturing process selection problem is a multi-attribute decision-making problem. These decisions are made during the preliminary design stages in an environment characterized by imprecise and uncertain requirements, parameters, and relationships. Material and process selection decisions must occur before design for manufacturing can begin. This paper describes a prototype material and manufacturing process selection system called MAMPS that integrates a formal multi-attribute decision model with a relational database. The decision model enables the representation of the designer's preferences over the decision factors. A compatibility rating between the product profile requirements and the alternatives stored in the database for each decision criteria is generated using possibility theory. The vector of compatibility ratings are aggregated into a single rating of that alternative's compatibility. A ranked set of compatible material and manufacturing process alternatives is output by the system. This approach has advantages over existing systems that either do not have a decision module or are not integrated with a database.     

A symbol-based intelligent control system with self-exploration process

This paper presents a symbol-based intelligent control system (SyICS) with a self-exploration process. The SyICS is comprised of a symbolic controller, a percepter, and a self-adaptor, and is a rule-based control system with on-line parametric adaptation. The symbolic controller consists of a number of symbolic rules, such as IF–THEN rules, for controlling the plant. The percepter is a sensory mechanism to perceive the control efficiency. Once the sensory information is found to be improper, i.e., there is inefficient control, the self-adaptor will be activated; otherwise, the symbolic controller will keep on the controlling assignment. The self-adaptor is an adaptive mechanism to explore the new symbolic rules and update the knowledge base for on-line and real-time adaptation. The self-exploration process is applied for the self-adaptor, and the hybrid genetic algorithm with variable-length chromosome is presented to fulfill the self-exploration process. The advantages of the SyICS are: (1) the symbolic controller is intuitive and easy to implement, and (2) The mechanism of the on-line adaptation is adopted and performed by the efficient hybrid genetic algorithm. A robotic path planning application is used to demonstrate the SyICS approach by comparing it with other intelligent control methods. The simulation results show that the robotic paths of SyICS model are the most efficient for all cases based on the path's efficiency measure.