A constrained EPSAC approach to inventory control for a benchmark supply chain system

The design of an appropriate inventory control policy for a supply chain (SC) plays an essential role in tempering inventory instability and bullwhip effect. Several constraints are commonly encountered in actual operations so managers are required to take these physical restrictions into account when designing the inventory control policy. Model predictive control (MPC) appears as a promising solution to this issue, due to its capability of finding optimal control actions for a constrained SC system. Therefore, the inventory control problem for a benchmark SC is solved using the extended prediction self-adaptive control approach to MPC. To extend methodologies in our previous work, the control framework relies on generic process model and incorporates the physical constraints arising from practical operations to form the general constrained optimisation problems. The managers can choose from decentralised and centralised control structures according to specific informational and organisational factors of their SCs. The proposed control schemes in this study may be appropriate for industrial practice because the designed policy can bring a reduction of over 30% in operating cost and a significant increase of customer satisfaction level compared with that of the conventional policy.     

Service levels,system cost and stability of production–inventory control systems

Production-inventory control system models have been analysed in the literature either in terms of their stability against demand fluctuations or in terms of their service level and cost performance under uncertain demand. This article analyses the production-inventory system performance in terms of service level (i.e. order fill rate) and average system costs, under stable settings of the control parameters. The classical automatic pipeline variable inventory and order-based production control system has been modified by explicitly modelling safety stock to help achieve higher services levels in the face of random demand. The stability of the system is affected by the control parameters: fractional rates of adjustment of work-in-process and inventory. However, the service level and average cost are affected by the control parameters as well as the smoothing factor in demand forecasting. This article puts forward five propositions which give light to general system performance based on the parameters selection. Intensive simulation experiments have also been carried out to reveal the performance variations within the stable region, leading to further insights on the system behaviour. The managerial insights which can assist proper tuning of systems to help achieve the desired performances have been discussed.     

Using cooling load forecast as the optimal operation scheme for a large multi-chiller system

Energy saving is one of the most important issues in high-tech manufacturing industries, such as semiconductor and electronics, because large chilled water systems are used to satisfy big cooling load requirements. In this paper, a new optimal integrity scheme based on a two-stage strategy, including a scheduling stage and an operating stage, is proposed to minimize the system energy consumption within a future time period. Instead of a lag scheme used in the general method, a forecasting scheme consisting of a series of optimal schemes at each sub-time period is also proposed for the two-stage design. The performance of the proposed method is examined through an industrial case. The cost of the proposed method is much less than that of the conventional method, so the proposed method is cost-efficient in applications of large air-conditioning systems.     

Towards intelligent manufacturing planning and control systems

In this paper, we review some well-known manufacturing planning and control (MPC) systems and models, and highlight both their advantages and major drawbacks. The analysis indicates that various important planning and control problems, as they arise in industry, are not properly addressed by current MPC systems. A well-known production system typology, illustrated by industrial examples, is briefly discussed to further highlight these planning and control problems. Next, we define a basic framework architecture for planning and control in both make-to-stock and make-to-order systems. The emphasis in this framework is on an integration of technological and logistics planning, and on an integration of capacity planning and materials coordination issues. In addition to this architecture, we further define an algorithmic framework that explicitly aims at the latter integration. To complete the architecture, we suggest a variety of procedures and algorithms to implement in the various modules.     

Development of metric method and framework model of integrated complexity evaluations of production process for ergonomics workstations

Staff in manufacturing sites not only need certain physical requirements for their allotted tasks but also utilise a large amount of information processing in the looming industrial age 4.0. This work established the Principles of Information Processing Economy in the production process and proposed a framework model of integrated complexity evaluation method for the production process, which combines both physical and cognitive loads while accounting for the effect of time stress. The method proposed in this study can be used for ergonomics evaluation of workstations. Compared with traditional evaluation methods, this method has good flexibility to account for the changes in labour loads in the industrial 4.0 eras and the role of various intelligent auxiliary systems. The proposed operational framework model can provide useful information for task assignment, operator selection and training, work organisation, and performance prediction.     

Integrated analysis of quality and production logistics performance in manufacturing lines

This paper presents an analytical method for evaluating the performance of production systems, jointly considering in a unique framework quality and production logistics performance measures. In the literature, quality and production logistics have traditionally been investigated using independent approaches. Thus far, only a few recent contributions have focused on their mutual inter-relation, showing that benefits can be achieved from an integrated analysis. This paper contributes to this growing research by considering, for the first time, production systems in which the behaviour of the machines is monitored by statistical control charts. The control action performed by the quality control system on the machines is directly modeled. Moreover, the impact of the quality control action on the logistic flow of parts in the system is taken into account. In order to estimate the performance of such systems, an approximate analytical method based on the system decomposition technique is developed. The accuracy of the method is assessed by comparing the results with those obtained by simulation. Analysis of the results provides new insights into the relations among the quality and production logistics performance measures and paves the way to the development of integrated design techniques for improved configurations of the system as a whole.     

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.     

A Spatiotemporal Method for the Monitoring of Image Data

Machine vision systems are increasingly being used in industrial applications because of their ability to quickly provide information on product geometry, surface defects, surface finish, and other product and process characteristics. Previous research for monitoring these visual characteristics using image data has focused on either detecting changes within an image or between images. Extending these methods to include both the spatial and the temporal aspects of image data would provide more detailed diagnostic information, which would be of great value to industrial practitioners. Therefore, in this article, we show how image data can be monitored using a spatiotemporal framework that is based on an extension of a generalized likelihood ratio control chart. The performance of the proposed method is evaluated through computer simulations and experimental studies. The results show that our proposed spatiotemporal method is capable of quickly detecting the emergence of a fault. The computer simulations also show that our proposed generalized likelihood ratio control charting method provides a good estimate of the change point and the size/location of the fault, which are important fault diagnostic metrics that are not typically provided in the image monitoring literature. Finally, we highlight some research opportunities and provide some advice to practitioners. Copyright © 2012 John Wiley & Sons, Ltd.     

A Robust Transfer Dictionary Learning Algorithm for Industrial Process Monitoring

Data-driven process-monitoring methods have been the mainstream for complex industrial systems due to their universality and the reduced need for reaction mechanisms and first-principles knowledge. However, most data-driven process-monitoring methods assume that historical training data and online testing data follow the same distribution. In fact, due to the harsh environment of industrial systems, the collected data from real industrial processes are always affected by many factors, such as the changeable operating environment, variation in the raw materials, and production indexes. These factors often cause the distributions of online monitoring data and historical training data to differ, which induces a model mismatch in the process-monitoring task. Thus, it is difficult to achieve accurate process monitoring when a model learned from training data is applied to actual online monitoring. In order to resolve the problem of the distribution divergence between historical training data and online testing data that is induced by changeable operation environments, a robust transfer dictionary learning (RTDL) algorithm is proposed in this paper for industrial process monitoring. The RTDL is a synergy of representative learning and domain adaptive transfer learning. The proposed method regards historical training data and online testing data as the source domain and the target domain, respectively, in the transfer learning problem. Maximum mean discrepancy regularization and linear discriminant analysis-like regularization are then incorporated into the dictionary learning framework, which can reduce the distribution divergence between the source domain and target domain. In this way, a robust dictionary can be learned even if the characteristics of the source domain and target domain are evidently different under the interference of a realistic and changeable operation environment. Such a dictionary can effectively improve the performance of process monitoring and mode classification. Extensive experiments including a numerical simulation and two industrial systems are conducted to verify the efficiency and superiority of the proposed method.     

Adaptive PID control based on explicit criterion minimization

Abstract

PID control has been widely used in industry for a long time. Under certain circumstances, it is necessary to retune the PID controller to obtain good performance. Recently, the developments in modern control theories and computing techniques have made automatic tuning of the PID controller feasible which provides better performance. In this paper, an adaptive PID controller based on explicit criterion minimization having the same structure as conventional PID controller is proposed. This new controller's design is based on the method of Ljung and Trulsson. Various properties of the method are described. Simulation studies using the new method show that the performance is satisfactory for control of minimum phase and nonminimum phase systems.     

An image-based multivariate generalized likelihood ratio control chart for detecting and diagnosing multiple faults in manufactured products

Image-capturing systems are increasingly being used in manufacturing shop floors since they can reliably capture important aesthetic information pertaining to the quality of manufactured parts in real time. State-of-the-art image-monitoring applications have focused on the detection of a single fault; however, the number of fault clusters per image in industrial applications can be numerous. To address this issue, we propose the use of a multivariate generalized likelihood ratio (MGLR) control chart for monitoring industrial products whose quality is described by a specific pattern (e.g. uniform patterns in LED screens or decorative patterns in textile products). Our method is specifically designed for greyscale images that are typical outputs of real-time industrial image-capturing systems. Extensive computer simulations show that the proposed method can detect the occurrence of single and multiple faults. We also present an experimental study to highlight how practitioners can implement and make use of the MGLR control chart in image-monitoring applications.     

Efficient and robust model predictive control for first swing transient stability of power systems using flexible AC transmission systems devices

A wide area measurement, nonlinear, model predictive control (MPC) approach is introduced to provide first swing stability protection of vulnerable power system transmission lines. The authors consider large disturbance events and focus on the avoidance of first swing angular separation using flexible AC transmission systems (FACTS) devices. The presented control strategy for FACTS devices is designed to be numerically efficient (due to the short MPC horizons) and robust (against complicated separation mechanisms). Simulation studies conducted on a three-machine system illustrate that the proposed MPC approach achieves first swing large disturbance performance that is near optimal and superior to existing transient stability controllers. Moreover, the proposed control approach is demonstrated to improve critical clearance times and to improve transfer capacity in simulation studies on the 39 bus New England system.     

非线性时变结构随机地震响应最优多项式控制

以随机地震动作用下具有Bouc-Wen滞回特性的非线性结构系统为受控对象,开展了最优多项式控制算法研究：包括系统矩阵中Maclaurin展开取初始零值衍生的具有时不变增益矩阵的控制律,和系统矩阵中Maclaurin一阶展开衍生的具有时变增益矩阵的控制律。研究表明,受控结构层间位移响应的变异性明显降低,结构的安全性显著提高。同时,基于时不变增益矩阵的控制律的控制效果在一定程度上受制于控制力施加的大小与系统稳定性之间的平衡关系,而考虑了每一个时间步位移和速度对增益矩阵影响、基于时变增益矩阵的控制律则能以较小的控制出力获得较好的控制效果。     

运筹学在工业工程中的应用

调查研究了运筹学模型及其方法在工业工程的应用情况。针对工程制造与控制系统中的存在的实际问题,研究了解决这些问题的特定运筹学的方法。文中还就运筹学方法今后的应用发展力作了探讨。     

Manufacturing planning and control approaches: market alignment and performance

The design of manufacturing planning and control (MPC) systems is a strategic decision for manufacturing operations. In this paper we analyze the interrelationships between the choice of MPC approaches at different hierarchical levels with market requirements and operational performance. These relationships are explored through an extensive survey comprising responses from 128 manufacturing firms. The results show that the choice of MPC approaches, primarily at the sales and operations planning and master scheduling levels, has a significant mediating role in improving performance. The alignment between market requirements and the choice of MPC approaches is significant and has a significant impact on performance. In a dynamic environment, the choice of MPC approaches is shown to have a positive mediating effect on operational performance.     

Vibration analysis diagnostics by continuous-time models: A case study

In this paper a forecasting system in condition monitoring is developed based on vibration signals in order to improve the diagnosis of a certain critical equipment at an industrial plant. The system is based on statistical models capable of forecasting the state of the equipment combined with a cost model consisting of defining the time of preventive replacement when the minimum of the expected cost per unit of time is reached in the future. The most relevant features of the system are that (i) it is developed for bivariate signals; (ii) the statistical models are set up in a continuous-time framework, due to the specific nature of the data; and (iii) it has been developed from scratch for a real case study and may be generalised to other pieces of equipment. The system is thoroughly tested on the equipment available, showing its correctness with the data in a statistical sense and its capability of producing sensible results for the condition monitoring programme.     

多开关磁阻电机无轴传动系统同步控制方法

目的解决多开关磁阻电机同步控制中输出功率不平衡的问题,提高印刷业的生产效率和产品质量。方法在传统交叉耦合同步策略的基础上,提出一种基于神经元变结构PID控制的同步控制方法,该控制策略用一个神经元控制器实现变结构PID控制,同时用另一个神经元控制器实时调整变结构PID控制器的参数,从而保证2台开关磁阻电机的输出功率相同。结果通过仿真数据分析,其达到稳态的调节时间和动态响应时间比现有的同步控制小,且抗干扰能力也得到了提高。结论该策略可提高多电机同步控制系统的同步跟随性能和抗干扰性能,增强多电机无轴传动的同步协调控制能力。     

A Risk‐based Approach to Managing Performance‐based Maintenance Contracts

The global trend towards performance‐based maintenance contracting has presented new challenges to maintenance service providers as they are compensated or penalized based on performance outcomes instead of time and materials consumed during maintenance service. The problem becomes more complex when uncertainties exist in reliability performance and maintenance activities of technical systems. In this paper, a general framework for managing performance‐based maintenance contract under risks is proposed. We illustrate our approach with an application in a multi‐echelon multi‐system spare parts control problem. Several different performance measures are considered and a probabilistic constrained optimization problem is formulated from the perspective of the service provider. Hybrid simulation/analytic heuristics are proposed to solve the problem based on the monotonic properties of performance measures. This approach is flexible and can be applied to a wide range of problems with similar properties. Numerical example shows that the probability of violating performance requirements is high if the risk is overlooked. We also provide guidelines on how to apply this approach in practice. Copyright © 2016 John Wiley & Sons, Ltd.     

Use of advance demand information in multi-stage production-inventory systems with multiple demand classes

This paper considers three-stage production-inventory systems serving two customer classes, where only one class provides advance demand information and early order fulfilment is acceptable. We propose a new approach for production replenishment and order fulfilment in such systems that uses advance demand information for performance improvement. The approach combines the benefits of early fulfilment and Kanban-based pull systems. Simulation is used to establish the performance of the resulting policy vs. two existing policies, for a variety of production scenarios and cost structures. A lower bound on total cost is also established using a simulation-based procedure. In general, early fulfilment with one-for-one replenishment is shown to provide greater benefit than making items to order. Neither of the existing policies, however, was found to use advance demand information as effectively as the proposed approach, which outperformed the existing policies in every case considered. Additionally, the proposed policy has the advantage of both retaining its benefit at high levels of system utilisation and increasing benefit up to the maximum level of advance demand information provided.     

柔性结构振动预测控制的仿真研究

针对柔性结构的振动问题，提出了用预测控制方法来实现对振动的主动控制。建立了由压电作动器和应变片传感器组成的悬臂梁实验系统的控制模型，用动态缩聚的方法对梁的有限元模型进行降阶，根据这个降阶模型设计了一个预测控制器，将其应用于系统的振动控制，并给出了预测步长和控制步长对控制性能的影响。仿真结果表明该预测控制方法能够有效地抑制柔性结构的振动。