An economic model for determining the optimal quality and process control policy in a queue-like production system

This paper interrelates and synthesizes the economic design of quality and process control policy and the management of a production system described in terms of an M/G/X queue. A mathematical model is developed to determine the optimal quality and process control policy when both the quality and quantity issues in the production system are considered. The optimal control policy is defined as the one that maximizes the expected profit per unit time over an infinite horizon. Hypothetical data is used to illustrate the impact of on-line control policies on the operating characteristics of the production process.

For a given control policy, it is shown that the expected profit per unit time of the production system can be increased by either improving the reliability of the production system, increasing the arrival rate of incoming jobs, increasing the system's processing rate, or shortening the system's shutdown time. The results also indicate that the larger the performance difference between the in-control and the out-of-control states, the greater the amount of effort should be involved in quality and process control. Finally, it is important for the capacity design of a production system to take into account the requirrments for both quality control and process adjustment.     

Optimally maintaining an M/G/1-type production system

The concept of more maintenance effort (or training) implying higher system reliability (or efficiency) is well accepted. In this paper we study an optimal maintenance (training) program based on this concept for a simple production system using the M/G/l vacation queue model. We discuss how to determine the optimal maintenance (training) time to minimize the average time spent by a job in the system.     

Simultaneous determination of preventive maintenance and replacement policies in a queue-like production system with minimal repair

This paper addresses the joint effects of preventive maintenance and replacement policies on a queue-like production system with minimal repair at failures. We consider a policy which calls for a preventive maintenance operation whenever N parts have been processed. If a failure occurs and at least K preventive maintenance operations have been carried out, the system is replaced by a new one. Otherwise, a failure is handled by minimal repair. An analytical model is developed and the argument of renewal–reward theory is used to provide long-run expected profit per unit time for a given maintenance and replacement policy. Numerical examples are given to provide some managerial insights.     

Simple fiber-optic-based sensors for process monitoring: an application in wine quality control monitoring

The goal of this research was to develop a simple and economical fiber-optic sensor technology for agrifood process monitoring. Toward this end, two fiber-optic sensors were developed to be used in combination: a single reflection V-bend sensor and a single fiber air-gap probe. The former is designed to be sensitive toward refractive index and the latter towards absorption. Experiments indicate that the micromachined V-bend fiber refractometer is most sensitive when the bend angle is centered around 140 degrees, at which angle the sensor may resolve changes in refractive index as small as 0.00015. Additionally, the V-bend sensor was found to be non-responsive toward sample absorption even in extremely absorbing solutions. The air-gap design absorption sensor, most commonly used for measurements in highly colored media, was found to be slightly sensitive towards refractive index. When the two sensors are used together, the response of the absorption sensor may be corrected for. This sensor combination is able to provide accurate measurements in situations where Beer's law is not obeyed. Results are presented that show that the sensor pair was successfully used to monitor wine sugar content (Brix), and color density and hue, parameters related to the age of the wine.     

Integrated maintenance and production control of a deteriorating production system

We consider a make-to-stock production/inventory system consisting of a single deteriorating machine which produces a single item. We formulate the integrated decisions of maintenance and production using a Markov Decision Process. The optimal dynamic policy is shown to have a rather complex structure which leads us to consider more implementable policies. We present a double-threshold policy and derive exact and approximate methods for evaluating the performance of this policy and computing its optimal parameters. A detailed numerical study demonstrates that the proposed policy and our approximate method for computing its parameters perform extremely well. Finally, we show that policies which do not address maintenance and production control decisions in an integrated manner can perform rather badly.     

Integrated production,statistical process control,and maintenance policy for unreliable manufacturing systems

The objective of this paper is to develop an integrated approach for the joint control of production, maintenance and quality for batch manufacturing systems. We consider such systems that are subject to degradation which is at the origin of the production of defective units. The quality control of lots produced is performed using an ‘x-bar’ control chart. This graphical tool will allow estimating the quality of the batch being produced and possibly undertake perfect preventive or corrective maintenance actions on the production system. A buffer stock is built to maintain continuity of supply during maintenance actions. The incurred total cost includes setup cost, inventory costs, the cost of unused products, maintenance costs and quality costs. Decision variables include the buffer stock size, the sample size, the sampling interval, the surveillance and the control limits of the control chart. Numerical experiments and sensitivity analyses are provided to evaluate the effectiveness of the proposed control policy and the robustness of the solving approach.     

Multivariate statistical monitoring of an industrial SBR process. Soft-sensor for production and rubber quality

This work presents a full methodology to build and evaluate a soft sensor capable of monitoring the production of Styrene-Butadiene Rubber (SBR) in an industrial train of 7 continuously-stirred tank reactors. The aim is to develop a device for on-line estimation of production and quality variables using a multivariate statistical technique like partial least squared (PLS). Besides pursuing the soft sensor development, this paper attempts to provide a guide for similar developments by suggesting attention to several specific methodological points. In this regard, the following features are highlighted: i) since a wide range validation space is desired for this sensor and the actual plant cannot be arbitrarily disturbed, an existing complex fundamental model is used to explore different possible operating conditions; ii) the approach used to develop the soft sensor includes a distributed sampling of multivariate steady-state conditions to collect the calibration data set, and the use of a filter for excluding outliers; and iii) it is shown that the analysis of how the explained variability progress when latent variables are included in the model allows the detection of poor predictor variables providing the chance for improving the multivariable regression by eliminating interfering contributions. Few after-modeling techniques are also suggested to confirm the consistency of the calibrating data set and the model precision over the applicability domain.     

Manufacturing quality density,control and maintenance

The purpose of this paper is to define conceptually and operationally, a measure of quality density in manufacturing. This is expressed in terms of a manufacturing process propensity to ‘output’ units which are defectives, as a function of the manufactured production output, the manufacturing deterioration process, maintenance, quality control, and generally the risks a manufacturing process is subjugated to. Particularly, we assume that the production process induces ‘shocks’ which lead to poorer manufactured quality, while maintenance efforts are continually being employed to restore the process propensity to produce units of better quality. Quality control is used then to monitor the output quality of units produced. Using a methodology of level crossing in stochastic point processes, the stationary probability distribution of a manufactured output quality is defined. Applications to production quality management, combined quality and maintenance management, as well as quality control are considered. Finally, an exponential shock model is resolved analytically.     

Environmental issue in an integrated production and maintenance control of unreliable manufacturing/remanufacturing systems

This paper addresses a joint production and maintenance problem under environmental constraints and reliability issues in a manufacturing/remanufacturing context. The manufacturing system is composed of one machine producing one type of product. The remanufacturing system, also composed of one machine, retrieves returned products from the market in order to refurbish them. The manufacturing and remanufacturing systems aim to satisfy random demands under a given service level. Moreover, the entire system generates harmful emissions. Exceeding carbon emission limits defined by authorities may risk sanctions. We aim to propose a compromise between ecologic and economic production and maintenance plan by calling on green subcontracting in order to satisfy the demand and avoid emission excess. Three models are proposed in this paper. These models tackle mainly the basic production problems and propose alternative equivalent solution schemas for future extensions. The robustness and usefulness of the proposals are illustrated with various examples and sensitivity analyses.     

Joint optimisation of production,maintenance and quality for batch production system subject to varying operational conditions

This paper considers the integration problem of production, maintenance and quality for a capacitated lot-sizing production system subject to deterioration. The effects of varying operational conditions from batch to batch on system reliability and product quality are modelled by proportional hazards models, resulting in non-monotonic failure rate and defect rate. After each batch production, imperfect preventive maintenance (PM) is determined to mitigate the system deterioration, and inspection is taken to sort nonconforming items in the finished goods. Once the cumulative number of nonconforming items exceeds a predetermined threshold, an overhaul is performed to renew the system. An integrated model for optimising production plan, PM plan and overhaul strategy is developed to minimise the total cost while satisfying all product demands. A genetic algorithm is proposed to solve the integrated model efficiently. Numerical results validate the rationality of the model with varying operational conditions consideration and its applicability in economic benefits.     

Statistical process control via context modeling of finite-state processes: an application to production monitoring

Conventional Statistical Process Control (SPC) schemes fail to monitor nonlinear and finite-state processes that often result from feedback-controlled processes. SPC methods that are designed to monitor autocorrelated processes usually assume a known model (often an ARIMA) that might poorly describe the real process. In this paper, we present a novel SPC methodology based on context modeling of finite-state processes. The method utilizes a series of context-tree models to estimate the conditional distribution of the process output given the context of previous observations. The Kullback-Leibler divergence statistic is derived to indicate significant changes in the trees along the process. The method is implemented in a simulated flexible manufacturing system in order to detect significant changes in its production mix ratio output.     

Optimal buffer inventory and preventive maintenance for an imperfect production process

In this paper we present a model to determine the optimal length of continuous production periods between maintenance actions and the optimal buffer inventory to satisfy demand during preventive maintenance or repair of a manufacturing facility. We include in the model the possibility of imperfect production. We consider that the duration and cost of the maintenance action depend on the state of the production facility.     

半马尔可夫过程在GI/M/1和M/G/1排队系统中的应用

本文运用齐次可列半马尔可夫过程的向后方程和向前方程,分别研究了GI/M/1和M/G/1排队系统队长的瞬时分布.首先得到了GI/M/1队长的转移概率的拉普拉斯变换满足的向后方程组,然后得到了M/G/1队长的转移概率的拉普拉斯变换满足的向前方程组,所得方程组的系数矩阵都是拟下三角矩阵,都可以通过迭代法进行求解.     

Economic design of an attributes control system for a multistage serial production process

A model for the economic design of an np-control system integrated within a multiple stage serial production process is presented. The total expected quality control cost includes the costs of sampling, the costs of investigating an out-of-control alarm and possibly correcting an assignable cause(s), and the costs associated with the production of non-conforming items. The model is represented as a directed network with decision variables of sample size, rejection number and frequency of sampling occurring at each stage of the process. A combination of dynamic programming and direct search techniques is applied to determine the set of sampling policies which yield minimum total expected cost. Numerical examples and results of a sensitivity analysis are reported.     

混凝土试件的制作、养护、质量检查

介绍了混凝土试件的制作养护和质量检查步骤,为保证施工单位制作合格的混凝土试件,确保混凝土的工程质量符合设计要求,提供借鉴。     

Integrating statistical process control,engineering process control and Taguchi's quality engineering

In this paper, a scheme is proposed to integrate statistical process control (SPC), engineering process control (EPC) and Taguchi's quality engineering (TQE). Then, two models are proposed to implement the proposed scheme. The models employ the concept of Taguchi's quadratic loss function to determine whether to take an EPC action by comparing the cost of the action and the cost of quality. A case study is used to compare these two models with the model in the literature where SPC and EPC have been integrated. The results have shown that the first model resulted in about a 25% saving and the second model resulted in even greater saving of about 30% for the case under consideration.     

一般限量服务M/G/1型单重休假排队系统的随机分解

本文研究了M／G／1型一般限量服务单重休假排队系统,根据稳态下M／G／1型非空竭服务休假排队系统的队长的随机分解的一般结构,提出简便算法一结构分析法,并且在先到先服务规则下(FCFS)求得稳态下队长的随机分解的概率母函数(GFP)和服务时间的随机分解的Laplace变换(LST),还充分地讨论了系统平稳的条件及其概率含义。     

工业过程监控系统中实时数据库的应用接口技术

针对工业实时数据库在某石化企业中的应用,提出了一套实时数据库与DCS及Web界面之间的接口方案。该方案是在Windows 2000 Server操作系统上,应用了WIN32中的多线程、匿名管道、WinSock等技术实现的。长时间的现场运行证明,该方案是可靠、稳定和有效的,达到了系统设计目标。     

Integrated production quality and condition-based maintenance optimisation for a stochastically deteriorating manufacturing system

This paper investigates the problem of optimally integrating production quality and condition-based maintenance in a stochastically deteriorating single- product, single-machine production system. Inspections are periodically performed on the system to assess its actual degradation status. The system is considered to be in ‘fail mode’ whenever its degradation level exceeds a predetermined threshold. The proportion of non-conforming items, those that are produced during the time interval where the degradation is beyond the specification threshold, are replaced either via overtime production or spot market purchases. To optimise preventive maintenance costs and at the same time reduce production of non-conforming items, the degradation of the system must be optimally monitored so that preventive maintenance is carried out at appropriate time intervals. In this paper, an integrated optimisation model is developed to determine the optimal inspection cycle and the degradation threshold level, beyond which preventive maintenance should be carried out, while minimising the sum of inspection and maintenance costs, in addition to the production of non-conforming items and inventory costs. An expression for the total expected cost rate over an infinite time horizon is developed and solution method for the resulting model is discussed. Numerical experiments are provided to illustrate the proposed approach.     

A quality growth model and its application to initial production process control

During initial production of a new product prior to actual production, the decrease in the fraction defective of units produced can be observed as personnel gather experience and the faults in the product's design, manufacturing, etc. are removed. This paper discusses an initial production process control based on a quality growth model proposed here. The model describes a continuing reduction in the cumulative defect rate defined by the ratio of the cumulative number of defective units to that of produced units. A stopping rule is also investigated for determining when to discontinue the initial control of the production process and proceed to the actual production stage. Further, a numerical example of the application is presented.