Design of predictable production scheduling model using control theoretic approach

As one of the most important planning and operational issues in manufacturing systems, production scheduling generally deals with allocating a set of resources over time to perform a set of tasks. Recently, control theoretic approaches based on nonlinear dynamics of continuous variables have been proposed to solve production scheduling problems as an alternative to traditional production scheduling methods that deal with decision-making components in discrete nature. The major goal of this paper is to improve predictability and performance of an existing scheduling model that employs the control theoretic approach, called distributed arrival time controller (DATC), to manage arrival times of parts using an integral controller. In this paper, we first review and investigate unique dynamic characteristics of the DATC in regards to convergence and chattering of arrival times. We then propose a new arrival time controller for the DATC that can improve predictability and performance in production scheduling. We call the new mechanism the double integral arrival-time controller (DIAC). We analyse unique characteristics of the DIAC such as oscillatory trajectory of arrival times, their oscillation frequency, and sequence visiting mechanism. In addition, we compare scheduling performance of the DIAC to the existing DATC model through computational experiments. The results show that the proposed system can be used as a mathematical and simulation model for designing adaptable manufacturing systems in the future.     

Fuzzy simulation approach to multi-task scheduling in uncertain distributed server systems

The efficient scheduling of tasks in distributed server systems is of great importance to minimise the response time and thus improve the performance of such systems. This paper presents an integrated fuzzy simulation approach to improve the performance of distributed server systems. Performance is defined in terms of time-varying distributions of job arrival, job parallelism and task service demand with fuzzy parameters. In order to achieve the most efficient policies for job scheduling in this fuzzy system, an integrated fuzzy simulation approach is used. This is the first study that uses fuzzy simulation for performance improvement of uncertain distributed server systems.     

基于Wiener-Hammerstein模型的一种系统辨识方法

针对工业大系统中Wiener-Hammerstein模型,提出一种新的辨识方法。该方法结合分散辨识对线性系统辨识精度高的优点与混合粒子群优化解决非线性、不可微和多峰值的复杂问题的长处,进行复合控制,并利用计量学中的动态计量方法,建立动态计量仿真模型。仿真研究与实验结果表明,该方法应用在非线性分布参数系统辨识中可有效提高辨识精度。     

Performance evaluation of a transportation-type bulk queue with generally distributed inter-arrival times

This paper is motivated by the performance evaluation of circulating vertical conveyor systems (CVCSs). CVCSs are bulk queues of transportation type. These material handling systems feature generally distributed inter-arrival times, which can be longer than the bulk service time. This leads to interdependencies between the number of arrivals in consecutive service intervals and the number of loads in the queue. We propose a new discrete-time approach for the steady-state analysis of such bulk service queues of transportation type with general arrival and service processes and finite server and limited queue capacities. The approach is based on a finite Markov chain that generates complete probability distributions for the key performance measures, including the queue length, waiting time and departing batch size. The proposed approach is exact in the cases of discrete-time slots, e.g. as in communication systems. We investigate the discretisation error that arises if the approach is used as an approximation for the continuous time using a numerical comparison to a discrete-event simulation. Moreover, we examine the impact of arrival stream variability on the system performance and compare the positive effects of a higher frequency of server visits with the effects arising from larger pickup capacities.     

Optimal search of distributed arrival time control

Distributed arrival time control (DATC) is a heuristic feedback control algorithm for scheduling which has been developed for a real-time distributed scheduling of heterarchical systems. It has been renowned not only for its fast solution searching algorithm but also for its flexibility to changing environment. However, the optimality of this heuristic method has not been analytically explained until recently because it has been designed to discover a near optimal solution instead of the true optimum. In this paper, we provide a novel optimal search method for the DATC scheduling problem by introducing a scalar cost function over the vector space of time and show the existence and location of true optima for the DATC scheduling problem through geometric approach. This geometrical interpretation enables us to find the true optimal by direct projection without iterations like previous DATC approaches. Based on the true optimum found, we evaluate the optimality of DATC algorithms by examining their dependency on initial conditions and explain their intrinsic causality mechanism for the discrepancy with true optimum. The implication of this study is on the new viewpoint over the vector space of DATC, which not only solves the optimality issue of DATC but also provides a new direction of direct search approach like projection method for the true optimum.     

Intercell scheduling: A negotiation approach using multi-agent coalitions

Intercell scheduling problems arise as a result of intercell transfers in cellular manufacturing systems. Flexible intercell routes are considered in this article, and a coalition-based scheduling (CBS) approach using distributed multi-agent negotiation is developed. Taking advantage of the extended vision of the coalition agents, the global optimization is improved and the communication cost is reduced. The objective of the addressed problem is to minimize mean tardiness. Computational results show that, compared with the widely used combinatorial rules, CBS provides better performance not only in minimizing the objective, i.e. mean tardiness, but also in minimizing auxiliary measures such as maximum completion time, mean flow time and the ratio of tardy parts. Moreover, CBS is better than the existing intercell scheduling approach for the same problem with respect to the solution quality and computational costs.     

Performance of real-time distributed arrival time control in heterarchical manufacturing systems

A highly distributed feedback control algorithm for autonomous part entities in heterarchical manufacturing systems is presented in this paper. A difference equation-based model is developed to analyze the discrete time dynamics of the resulting nonlinear control system. Control parameters are found analytically that guarantee that the system is bounded under disturbances. The dynamic response to: (i) changes in due dates; and (ii) the bulk arrival of parts is presented. The ability of the system to exponentially reduce the mean and variance of due-date deviation in the single machine case makes it an attractive option for real-time control of just-in-time production.     

A max-algebra approach to the robust distributed control of repetitive AGV systems

This paper presents a new approach for distributed control of automatic guided vehicle systems (AGVS) that uses max-algebra formalism to model system operation. The proposed method differs from previous works on performance analysis and control of such systems in that it constructs a feasible schedule by exploiting the repetitive character of the flow of automated guided vehicles. The AGVS is treated as a distributed system composed of autonomous and repetitive processes of AGV flows. Its periodic behaviour follows from the type of operation characterizing the job shops considered. The proposed approach employs a concept of asynchronous traffic semaphores that provide the local mechanism for vehicle flow synchronization. Setting the timing of particular semaphores results in distributed control of vehicle flows possessing self-synchronization capabilities.     

Real-time batch sequencing using arrival time control algorithm

This paper proposes a new feedback control method for batch sequencing in process industries where meeting customer due-date is important. Specifically, short-term batch sequencing for Just-In-Time is solved using an arrival time control approach. An integral controller embedded in each order adjusts the arrival time in real-time using the feedback obtained from a fast-mode simulation of the batch processing system. The applicability of the proposed batch sequencing method for the Penn State University Creamery is studied. Comparison of due-date performance with commonly used dispatching rules is presented. The proposed method has also been tested for general batch processing systems and has been found to produce good, feasible schedules with significantly better performance than the dispatching rules in terms of due-date deviation minimization.     

Design and operation of manufacturing systems: the control-point policy

This paper synthesizes recent work by the author and his colleagues on the performance analysis of manufacturing systems and on real-time scheduling methods. It describes a decentralized scheduling/control policy and proposes a method for analyzing the performance of systems that are operated according to the policy. It presents three views of the production system: surplus-based, time-based, and token-based; and shows how they are equivalent in special cases. While there are no assurances of optimality, experience suggests that the policy has desirable characteristics. The paper also suggests how the physical resources and the control policy can be designed together.     

Modelling of simulated moving bed adsorption system: a more precise approach

A mathematical model for a simulated moving bed adsorption system is presented using a more precise approach. In this precise approach the differential equations along with appropriate boundary conditions are written for each adsorption column as distinct from the section approach adopted by previous workers in order to examine the column dynamics of the actual system. An axially dispersed plug flow model with linear driving force rate expression for mass transfer and nonlinear Langmuir equilibria are considered. The time-dependent boundary conditions for each column are formulated and related to switching time. Computations are performed for several cycles till the cyclic steady state is reached. The results obtained from the present model for the limiting cases of linear glucose-fructose and nonlinear monoethanolamine-methanol systems are compared with available experimental data and are found to agree well. The effect of various process parameters on the performance of systems are investigated and the distinction from the section approach is emphasized. The present study reveals that the system performance and dynamics are strongly dependent on axial dispersion, eluent-to-feed ratio, bed length and switch time. It is observed that there exists a set of optimum values of all the parameters for best process performance, which can be evaluated from the present simulation.     

Look ahead job demanding for improving job shop performance

In this paper a new coordination approach for decentralized job shop scheduling rules is presented and analyzed in a simulation study. The coordination is based on look ahead information and contains a mechanism for demanding and supplying jobs. The simulation experiments show that the performance of conventional scheduling rules is significantly improved using the coordination mechanism.     

大型结构小增益分散稳定化容错控制研究

针对大型土木工程结构,研究了具有完整性的小增益分散稳定化容错控制问题,考虑子控制系统关联项及系统中传感器与作动器出现故障的情况,利用Lyapunov稳定性理论及线性矩阵不等式方法,给出了离散时滞关联系统分散镇定的充分条件,并证明了该条件等价于一组线性矩阵不等式的可行性问题。进而,通过建立和求解一个凸优化问题,提出了具有完整性的小反馈增益参数分散稳定化容错状态反馈控制律的设计方法,所得到的子系统控制器能保持全局渐进稳定。针对ASCE 9层benchmark模型,该文分别从部分独立分散控制和重叠分散控制角度研究分析了正常工况、传感器失效、作动器失效及传感器作动器均失效工况的分散控制设计与数值分析。结果表明,该文提出的小增益分散稳定化控制（LMI-SGDSC）算法能获得与集中控制策略接近的控制效果,且无需更多的控制能量;相对于集中控制,重叠分散控制系统具有更高的可靠性;在发生故障时,具有完整性的分散稳定化容错控制（LMI-SGFTDSC）具有较好的控制效果。     

Proper lumping in systems biology models

An algorithm for automatic order reduction of models defined by large systems of differential equations is presented. The algorithm was developed with systems biology models in mind and the motivation behind it is to develop mechanistic pharmacokinetic/pharmacodynamic models from already available systems biology models. The approach used for model reduction is proper lumping of the system?s states and is based on a search through the possible combinations of lumps. To avoid combinatorial explosion, a heuristic, greedy search strategy is employed and comparison with the full exhaustive search provides evidence that it performs well. The method takes advantage of an apparent property of this kind of systems that lumps remain consistent over different levels of order reduction. Advantages of the method presented include: the variables and parameters of the reduced model retain a specific physiological meaning; the algorithm is automatic and easy to use; it can be used for nonlinear models and can handle parameter uncertainty and constraints. The algorithm was applied to a model of NF-kB signalling pathways in order to demonstrate its use and performance. Significant reduction was achieved for the example model, while agreement with the original model was proportional to the size of the reduced model, as expected. The results of the model reduction were compared with a published, intuitively reduced model of NF-kB signalling pathways and were found to be in agreement, in terms of the identified key species for the system?s kinetic behaviour. The method may provide useful insights which are complementary to the intuitive reduction approach, especially in large systems.     

Metamodels of production line transient behaviour for sudden machine breakdowns

Production controls based on mean value analysis and steady-state conditions are incapable of making on-time decisions that cope with unexpected dynamic events which are due to interruptions in complex work flow characteristic of modern production lines. One of the most significant dynamic events in production situations is a sudden machine/operator breakdown/outage. Computer simulation is known to be a useful tool for modelling the dynamic response of a system to machine breakdown, but it takes too long to perform its analysis to provide the response time necessary for control procedures. Analytical methods provide formulae which are suitable for real-time analysis, but there are no results available for transient behaviour associated with machine breakdown. Metamodelling is the process of summarizing the results of a simulation study in analytical form. In this paper, we present our metamodels for the dynamic behaviour of both time in system and number in system for a general arrival time, general service time, multi-station, multi-server production line system. The formulae are exponential in nature and are developed through a study of first-order differential equations from system control theory. The constants used in our results are determined off-line through discrete-event simulation analysis. The metamodels themselves are available to on-line users as a predictor of parts that will be delayed because of breakdown(s) as a function of time in the future. The integrated approach of using simulation for modelling system details and analytic method for describing the revealed system transient behaviour is a powerful methodology for analysing large-scale production systems.     

Model reduction for linear and nonlinear magneto‐quasistatic equations

We consider model reduction for magneto‐quasistatic field equations in the vector potential formulation. A finite element discretization of such equations leads to large‐scale differential‐algebraic equations of special structure. For model reduction of linear systems, we employ a balanced truncation approach, whereas nonlinear systems are reduced using a proper orthogonal decomposition method combined with a discrete empirical interpolation technique. We will exploit the special block structure of the underlying problem to improve the performance of the model reduction algorithms. Furthermore, we discuss an efficient evaluation of the Jacobi matrix required in nonlinear time integration of the reduced models. Copyright © 2017 John Wiley & Sons, Ltd.     

Integrating order release control with due-date assignment rules

This study integrates order release control methods with due-date assignment rules and assesses its impact on the accuracy of inter-operation time estimation and performance of due-date assignment. The assessment is made by using an experimental design with three due-date assignment rules, three scheduling rules and three order release models. The three order release models are: (1) Basic model, in which three due-date assignment rules consider the order arrival time as the order release time; (2) Control model, in which three due-date assignment rules integrate with the order release control method developed here; and (3) Adjustment model, in which the control model integrates with the order release control adjustment developed here. Simulation results in this study indicate that integrating the order release control method with due-date assignment rules will significantly enhance not only the accuracy of interoperation time estimation, but also the performance of due-date assignment rules.     

Repair-control of enterprise systems using RFID sensory data

This paper presents an architecture for implementing real-time enterprise planning, scheduling and control processes based on information provided by radio frequency identification (RFID) sensing systems. It introduces a new paradigm, called repair, for modeling enterprise processes that is based on the idea of incremental performance improvements and disruption minimization. The proposed model is expressed using differential equations with discontinuous right-hand sides. The repair framework is suitable for implementing enterprise feedback control systems that can easily be interfaced with an existing enterprise resource planning infrastructure. RFID sensing systems have the potential to provide the real-time data needed to implement enterprise feedback functionality.     

A fuzzy logic modelling of dynamic scheduling in FMS

This paper is concerned with scheduling in flexible manufacturing systems (FMSs) using a fuzzy logic (FL) approach. Four fuzzy input variables: machine allocated processing time, machine priority, due date priority and setup time priority are defined. The job priority is the output fuzzy variable, showing the priority status of a job to be selected for next operation on a machine. The model will first select the machines and then assign operations based on a multi-criteria scheduling scheme. The performance of the approach is compared against established methods reported in the literature. The performance measures considered average machine utilisation, meeting due dates, setup times, work in process and mean flow times. The test results demonstrate the superiority of the fuzzy logic approach in most performance measures.     

A distributed scheduling method for computer integrated manufacturing: the use of local area networks in cellular systems

This paper describes a distributed scheduling approach that takes into account characteristics of the communication network in the computer-integrated manufacturing environment. The approach is based on a network-wide bidding scheme wherein the scheduling decision is made by collecting the price of each manufacturing cell for taking on the job; different dynamic scheduling heuristics can be incorporated in this scheme and executed in a distributed fashion. This paper also describes the formalism and model for the distributed scheme that can be embedded in a communication protocol. A simulation study has been conducted to evaluate and compare the performance of different strategies or heuristics employed in the scheduling method.