An optimal production lot-sizing problem for an imperfect process with imperfect maintenance and inspection time length

This article develops an integrated model in considering the situations of an imperfect process with imperfect maintenance and inspection time for the joint determination of both economic production quantity (EPQ) and preventive maintenance (PM). This imperfect process has a general deterioration distribution with increasing hazard rate. Even with periodic PM, such a production system cannot be recovered as good as new. This means that the system condition depends on how long it runs. Also, the PM level can be distinct due to the maintenance cost. For convenience, it is assumed the age of system is reduced in proportional to the PM level. Further, during a production cycle, we need an inspection to see if the process is in control. This inspection might demand a considerable amount of time. In this article, we take PM level and inspection time into consideration to optimise EPQ with two types of out-of-control states. To see how the method works, we use a Weibull shock model to show the optimal solutions for the least costs.     

基于CPS框架的微粉生产过程多模型自适应控制

针对矿渣微粉（Ground granulated blast-furnace slag,GGBS）生产这一多变量、强耦合、多工况的复杂非线性过程,本文根据大量生产数据,提炼出矿渣微粉生产过程的三个典型工况.求解多工况多目标优化问题以求得最优设定值.建立多工况下的递归神经网数据驱动模型,并采用自适应动态规划方法,建立多个控制器,结合加权多模型控制,实现矿渣微粉生产过程在多工况切换情况下的自适应控制.通过过程运行优化、跟踪控制优化、通讯、工业以太网等信息资源与矿渣微粉生产物理资源之间的融合,构建基于信息物理系统（Cyber-physical system,CPS）的矿渣微粉生产优化控制系统.实验分析表明,本文提出的基于CPS的多模型自适应控制器,能够有效实现多工况条件下矿渣微粉生产过程的自适应控制,减小超调量,提高控制品质.     

Simultaneous determination of the optimal production–inventory and product inspection policies for a deteriorating production system

In this paper, we attempt to find a method for the optimization of production–inventory and product inspection policies for deteriorating production systems. Taking advantage of the nature of a deteriorating production system, a strategy would be not to inspect the first s items of the batch. Therefore, an inspection policy which disregards the first s (DTF-s) items of the batch is proposed. Under the DTF-s policy, we do not inspect the first s produced items but inspect only those items from the (s+1)th till the end of the production run. The objective of this study was the joint determination of the production lot size and the inspection policy s, resulting in a minimization of the expected average cost per unit time. Based on this model, the underlying conditions necessary for the existence of an optimal policy are given. Two commonly used inspection strategies, no inspection and full inspection are discussed. Under both inspection strategies, an optimal production–inventory lot is bounded by the traditional economic quantity. The case of full inspection is shown to be an extension of previously reported results. The option of investing in the process of quality improvement is also discussed. Finally, numerical examples are given to illustrate the method and its advantages in the conclusion.Scope and purposeThis paper considers the relationship between production, inventory and inspection in a deteriorating production system which may transit from the “in-control” state to the “out-of-control” state after a period of operation. Once the transition to the “out-of-control” state has occurred, it is assumed that some percentage of the items produced are defective or of substandard quality. However, in many cases, defects in a defective item can only be identified by an inspection process which carries an inspection cost. Those inspected items which are found to be defective are reworked at some cost before being shipped. On the other hand, defective items which are not inspected will be passed to the customer, incurring a much larger warranty cost. In order to operate such a system economically, tradeoffs among production setup, inventory, inspection and defective cost must be analyzed. Deterioration of the production system is an inherent process in all manufacturing industries. An understanding of the relationship among production, inventory and inspection for such systems will help managers to maintain efficient and economic control of operations.     

随机伺服系统自适应二次最优组合控制

本文基于极点在线优化原理和随机过程理论,针对缓时变随机伺服系统提出一种参数自 适应和二次性能最优的组合控制.这种控制形式简单、运算量小,能较好地适应系统的时变特 性,并保持系统在不同参数与工况下具有最佳跟踪性能.文章讨论了控制的收敛性,并通过仿 真和应用实例显示这种控制的有效性及良好的鲁棒性.     

Coordinated procurement/inspection and production model under inspection errors

In this study, we investigate integrating the acquisition of input materials, material inspection and production planning, where type I and type II inspection errors are allowed, and the unit acquisition cost is dependent on the average quality level. This study aims to find an optimal purchase lot size (or here, equivalently, the fixed production rate multiplied by the production run time), input quality level and the associated inspection policy that minimize the total cost per item including the order cost, materials purchase cost, setup cost, inventory holding cost, and the quality-related cost. Furthermore, the boundaries, conditions and properties for the optimal production run time are obtained under an optimal inspection policy when the input material quality level is fixed. These findings will facilitate the establishing of an efficient algorithm for an optimal solution. The study demonstrates that a partial inspection approach could dominate over both the commonly used policies of full or no inspection, which is different from a previous report where the optimal inspection policy is either full or no inspection. A numerical example is performed to evaluate the impact of the two types of inspection errors and the process deterioration because of a nonconforming process input on the optimal solution, where a Weibull shift distribution is used to simulate the process failure time. Finally, conclusions are addressed.     

Impact of inspection errors on the formulation of a multi-objective optimization process targeting model under inspection sampling plan

The literature on inspection systems has demonstrated that such systems are error prone. Such systems exhibit type I and type II errors. Type I error is classifying a conforming item as non-conforming while type II error is classifying a non-conforming item as conforming. The errors may arise from the measurement system or the inspectors. It is essential to assess the impact of the inspection errors on the optimal parameters and objective functions of process targeting models. The purpose of this paper is to assess the impact of the inspection errors on the optimal parameters and objectives functions values of Duffuaa and El-Ga’aly multi-objectives optimization model recently developed for process targeting (2013a). In order to accomplish the objectives of the paper, Duffuaa and El-Ga’aly multi-objective optimization model is extended by introducing the measurement errors in the inspection system and penalties to mitigate the effect of the errors. The results of the extended model is compared with the previous model and employed to studying the impact of the errors on the values of objective function and the optimal process parameters in a multi-objectives environment. The results indicated that inspection errors have significant impact on the profit and uniformity objectives.     

A methodology for joint optimization for maintenance planning, process quality and production scheduling

Performance of a manufacturing system depends significantly on the shop floor performance. Traditionally, shop floor operational policies concerning maintenance scheduling, quality control and production scheduling have been considered and optimized independently. However, these three aspects of operations planning do have an interaction effect on each other and hence need to be considered jointly for improving the system performance. In this paper, a model is developed for joint optimization of these three aspects in a manufacturing system. First, a model has been developed for integrating maintenance scheduling and process quality control policy decisions. It provided an optimal preventive maintenance interval and control chart parameters that minimize expected cost per unit time. Subsequently, the optimal preventive maintenance interval is integrated with the production schedule in order to determine the optimal batch sequence that will minimize penalty-cost incurred due to schedule delay. An example is presented to illustrate the proposed model. It also compares the system performance employing the proposed integrated approach with that obtained by considering maintenance, quality and production scheduling independently. Substantial economic benefits are seen in the joint optimization.     

Robust gain switching control of constant bottomhole pressure drilling

Automation of managed pressure drilling is crucial in order to enhance safety. This process is highly nonlinear and the system varies considerably with changes in drilling conditions. In this work we have analyzed the effect of various operating conditions on plant parameters and designed a controller which will deliver consistent performance for different working conditions and will also be robustly stable. The control objectives of robustness and good performance are achieved by using multiple robust loop shaping controllers. Based on choke opening and mud flow rate, an appropriate controller is selected by utilizing a gain schedule. An observer for estimation of the reservoir pressure is also implemented so that an appropriate bottom hole pressure setpoint can be selected to maintain overbalanced conditions.     

Economic ordering policy for an item with imperfect quality subject to the in-house inspection

This article considers a production/inventory system where each lot of items received or produced contains a random proportion of defective units, items of imperfect quality. The purchaser contacts a 100% inspection in order to identify the perfect (acceptable) quality items. The model examines the following two options for the imperfect quality items: sell them to a secondary market, as a single batch and at a price lower to that of new ones, or rework them at some cost and then use them as new ones to satisfy demand. After inspection, the good quality items are sent to the working inventory warehouse in batches of equal size. For both of these cases, the optimal ordering lot size and the optimal number of batches are obtained. A numerical example illustrates the solution procedure and sensitivity analysis results are reported.     

NDC纸张定量与水分在线检测系统的使用和维护

在生产高档纸的纸机中,纸张的定量和水分是影响纸张质量的两个重要参数,控制好这两个参数就能较好地保证产品的质量,增加产量和降低成本。使用好这台设备,在整个生产过程中起着至关重要的作用,本文介绍了怎样使用和维护NDC纸张定量与水分在线检测系统。     

Joint admission,production sequencing,and production rate control for a two-class make-to-order manufacturing system

Today's manufacturing industry faces a number of challenges related to the rapid delivery of products with a high degree of variety. Striking a balance between the effectiveness in capacity utilization and the rapidness in order-fulfillment is a substantial challenge for manufacturing companies. This work aims to provide a theoretical basis from which to address this practical question. To this end, we address the problem of coordinating the admission, production sequencing, and production rate controls for a two-class make-to-order manufacturing system. Formulating the problem as a Markov decision process model, we identify the structural properties of optimal control policies under both discounted and average profit criteria. We show that the cμ rule is optimal for production sequencing and the optimal admission and production rate control policies can be characterized by the state-dependent threshold levels, provided that the production times are not associated with customer class. We also show that the optimal production rates are monotone in the system state, as in the case of a single class queueing system, and that the lower priority class can be preferred to the higher priority class in order admission under a certain condition on the system parameters. Our numerical study demonstrates that a considerable economic benefit can be achieved if the production rate is dynamically controlled between the minimum and maximum rates rather than fixed to the mean rate of these values. Finally, we present a heuristic policy that is described by linear switching functions for the control of order admission and a selection rule for the control of production rate. We compare the performance of our heuristic to the optimal policy using a numerical experiment, revealing that the heuristic provides near optimal solutions to test example problems and is robust to the system parameters.     

A two-stage hybrid manufacturing model with controllable make-to-order production rates

As an effective strategy to facilitate delivering customized products within short lead time, hybrid manufacturing via a two-stage process has received attention from academia and industry. In this paper, we study a two-stage hybrid manufacturing system in which semifinished products are manufactured in a make-to-stock fashion in the first stage and end-products are produced from semifinished goods in a make-to-order (MTO) mode in the second stage. The rate of MTO production can be controlled within given limits, depending on the status of the system. The primary goal of this paper is to study a policy for coordinating order admission, MTO production rate, and inventory replenishment controls. Formulating the problem as a Markov decision process model, we characterize the structure of optimal control policies to maximize the long-run average profit. Using a numerical experiment, we study how the flexibility in MTO production rate affects the optimal policy and the optimal profit. We also examine the effect of the number of alternative MTO production rates on the optimal profit. We propose three heuristic policies implementable for general cases. The first heuristic describes two linear switching functions for admission and production controls and a selection rule for MTO production rate control. The second heuristic specifies fixed thresholds for the control decisions using the local information. The third heuristic presents linear switching functions that approximate the optimal threshold curves. Unlike second and third heuristics, the first heuristic does not require a grid search to determine the control parameters. We implement numerical studies to examine the marginal impact of system parameters and the effect of the number of alternative MTO production rates on the performance of the heuristics. Compared to the optimal policy, the average percentage performance of the first and third heuristics is less than 1% for both numerical studies. On the other hand, the average percentage performance of the second heuristic is larger than 3%, and it exceeds 10% for a set of particular problem examples.     

基于模糊规则与CBR的磨矿专家控制方法

为了解决磨矿过程这一典型的复杂工业过程的优化控制问题,基于某选矿厂的两段全闭路磨矿流程展开研究,提出了基于模糊规则和案例推理相结合的磨矿专家系统控制方法,解决了实际应用中案例检索相似度较低,无法求解的问题.同时,为了进一步提高模型的准确性,解决由于检索到的案例与当前工况之间的差异导致的案例解之间存在差别的问题,采用RB...     

Optimal control strategy of working condition transition for copper flash smelting process

Because there are large state fluctuation of working conditions, excessive energy consumption caused by manual operation in the dynamic transient procedure for copper flash smelting process. Working conditions of copper flash smelting process must be adjusted to the complex and variable copper concentrate feeding to satisfy the smelting performance. Optimal control strategy based adjustment cost for copper flash smelting working condition transition is proposed, which can achieve the expected working condition by following the optimal working condition transition path. The Cauchy–Schwarz inequality-based two-level matching method is developed to set the expected working condition. Then with minimizing adjustment cost and restricting operation domain to optimize smelting performance indicators, the optimal control problem of working condition transition is converted into a multi-constraints optimization problem with two fixed ends. A Legendre pseudospectral-based optimization method is also presented to obtain the path of optimal working condition transition. The simulation results of actual production data collected are given to verify the effectiveness and feasibility of the proposed strategy.     

Optimal lot size and offline inspection policy

In this study, we investigate the effects of using process status at the end of the production lot (PSPL), on determining the optimal policies for products inspection and production lot size. First, we obtain the optimal product inspection policies for different PSPL for a given lot in the in-control or out-of-control state. Properties for the inspection policy are explored. Then, the expected total cost function, which includes setup cost, process maintenance cost and quality-related control cost, is obtained. The optimal production lot size that minimizes the expected total cost per item is determined. Our proposed inspection policy is compared with the three policies of no inspection, full inspection, and disregarding the first s items policy, in which only items from s+1 until the end of the production lot are inspected. Differences in the minimum expected total cost per item between our proposed inspection policy and the other three policies are investigated with a numerical example.     

Economic production quantity models for deteriorating/imperfect products and service with rework

In this paper, two economic production quantity (EPQ) models are proposed for deteriorating/imperfect items with rework process. The production process is imperfect, and imperfect quality items are reworked to become serviceable. At the same time, the remaining good quality items may deteriorate. The inspection of deteriorated items is also imperfect, so that deteriorated items may be sold to customers, which will create negative impact on corporate image. In the first model, a single production-rework plant system is considered. The optimal production times and the economic production quantities are obtained analytically. In the second model, a system that consists of n production plants and one rework plant is considered. A solution procedure is developed in order to obtain the optimal operating cost. Numerical examples are provided to compare the performance of the two systems.     

The optimal location of inspection stations using a rule-based methodology

The location of inspection stations is a significant component of production systems. In this paper, a prototype expert system is designed for deciding the optimal location of inspection stations. The production system is defined as a single channel of n serial operation stations. The potential inspection station can be located after any of the operation stations. Non-conforming units are generated from a compound binomial distribution with known parameters at any given operation station.

Traditionally Dynamic programming, Zero-one integer programming or Non-linear programming techniques are used to solve this problem. However a problem using these techniques is that the computation time becomes prohibitively large when the number of potential inspection stations are fifteen or more. An expert system has the potential to solve this problem using a rule-based system to determine the near optimal location of inspection stations.

The prototype expert system is divided into a static database, dynamic database and knowledge base. Based on defined production systems, the sophisticated rules are generated by the simulator as part of a knowledge base. A generate-and-test inference mechanism is utilized to search the solution space by applying appropriate symbolic and quantitative rules. The goal of the system is to determine the location of inspection stations while minimizing total cost.     

Working in public health services in Brazil: the relationship between different rationalities

Success in a public health system is related to its ability to change its production process and to deal with general principles of the health system, such as universality and equity. The frameworks proposed by service marketing scholars have been developed primarily for private services; they focus on acceptance by the targeted client-users, and on the technical specifications of the new service delivery processes. Little attention has been given to the employees’ point of view and their activities to maintain service operations modulated by innovation. In a public health system, workers make decisions in real time related to users’ needs and the technical specifications of the process; therefore, it is very important to understand how the changes impact on employees’ activities and on the quality delivered for citizens. This article discusses how changes implemented in Sao Paulo, Brazil impact the organizational parameters and working activities for front-line workers.     

关于分程控制系统的研究

在石油化工生产过程中,为了满足特殊工艺的要求,分程控制系统得到越来越广泛的应用。本文对分程控制系统的工作原理进行了介绍,并对如何采用阀门定位器实现“硬分程”,在DCS@通过组态实现“软分程”进行了分析。     

Optimal inspection and economical production quantity strategy for an imperfect production process

This paper considers a problem relating to the integration of production, maintenance, inspection and inventory. The optimal inspection interval, inspection frequency and production quantity were studied, assuming an imperfect production process and a maintenance policy that permits minimal repair, shortages and inspection errors. When the process is in the in-control state, preventive maintenance is performed. If the process is in the out-of-control state, there are two possibilities. The first is a relatively mild production process shift, where minimal repair can bring the process back into the in-control state. The second possibility is a more serious shift, where minimal repair cannot bring the process back into the in-control state. In this case, it will be necessary to halt production and perform repair or replacement. It is accepted that, when a production process is in the out-of-control state, an amount of defective goods will be produced. Within the context of a deteriorating production process system, the advantages of preventive maintenance were explored, using numerical analysis to analyse the impact of inspection errors, permitted shortage conditions and minimal repair on cost.