Maintenance scheduling for a manufacturing system of machines with adjustable throughput

This paper considers the problem of analyzing and optimizing joint schedules of maintenance and throughput adjustment operations in manufacturing systems. The purpose of joint scheduling of maintenance and throughput changing operations is to maximize the cost benefits of maintenance operations in manufacturing systems in which some or all of the machines can execute their function under different process settings, resulting in different machine and system throughputs. Such a capability enables one to strategically slow down more degraded machines or accelerate freshly maintained machines so that production targets can be met and maintenance operations can be offset to times when they are less intrusive on the manufacturing process. A Monte-Carlo-simulation-based method is proposed for the evaluation of cost effectiveness of any schedule of maintenance and throughput changing operations, and a genetic-algorithm-based method is proposed to enable searching for schedules that would maximize the cost benefits of these operations. A matrix chromosome representation of the joint schedules of maintenance and throughput adjustment operations is introduced and several mechanisms of chromosome evolution and selection are proposed and analyzed in numerical simulations of such manufacturing systems. Results indicate a good ability for the newly proposed methods to achieve a tradeoff between cost benefits of production and losses due to maintenance operations through strategic allocation of maintenance and throughput changing actions.     

Maintenance resources optimization applied to a manufacturing system

This paper presents an availability optimization of an engineering system assembled in a series configuration, with redundancy of units and corrective maintenance resources as optimization parameters. The aim is to reach maximum availability, considering as constraints installation and corrective maintenance costs, weight and volume. The optimization method uses a Genetic Algorithm based on biological concepts of species evolution. It is a robust method, as it does not converge to a local optimum. It does not require the use of differential calculus, thus facilitating computational implementation. Results indicate that the methodology is suitable to solve a wide range of engineering design problems involving allocation of redundancies and maintenance resources.     

Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation

This paper tries to integrate sequential imperfect maintenance policy into condition-based predictive maintenance (CBPM). A reliability-centered predictive maintenance policy is proposed for a continuously monitored system subject to degradation due to the imperfect maintenance. It is assumed that the system hazard rate is a known function of the system condition and then can be derived directly through CBPM. A hybrid hazard rate recursion rule based on the concept of age reduction factor and hazard rate increase factor is built up to predict the evolution of the system reliability in different maintenance cycles. Whenever the system reliability reaches the threshold R, an imperfect preventive maintenance (PM) is performed on the system. The optimal reliability threshold R is determined by minimizing the cumulative maintenance cost per unit time in the residual life of the system which is based on simulation. Finally, a discussion is presented to show how the optimal results depend on the different cost parameters.     

An inspection model for a multi‐component system subject to 2 types of failures

Group maintenance is common and of significant importance for complex systems in industrial applications. This paper proposes a novel inspection and replacement model for a multi‐component system whose components are all subject to 2 typical failure modes, ie, catastrophic failure and minor failure. A catastrophic failure stops the system immediately, whereas a minor failure is not fatal and could only be identified by periodic inspection. At either a catastrophic or a minor failure, replacement is immediate. The maintenance cost model could be constructed through calculating the distribution of the “forward time”, which denotes the time elapse to a catastrophic failure since the previous inspection. The objective of this paper is to minimize the expected cost per unit time of the system via the optimization of the inspection interval. A case study on offshore wind turbine blades is presented to illustrate the maintenance model.     

Genetic algorithm optimisation of the maintenance scheduling of generating units in a power system

A new method for optimisation of the maintenance scheduling of generating units in a power system is developed. Maintenance is scheduled to minimise the risk through minimisation of the yearly value of the loss of load expectation (LOLE) taken as a measure of the power system reliability. The proposed method uses genetic algorithm to obtain the best solution resulting in a minimal value of the annual LOLE value for the power system in the analysed period. The operational constraints for generating units are included in the method. The proposed algorithm was tested on a Macedonian power system and the obtained results were compared with the results received from the approximate methodology. The results show the improved reliability of a power system with the maintenance schedule obtained by the new method compared to the results from the approximate methodology.     

Real-time scheduling in manufacturing system with machining and assembly operations: a state of art

Manufacturing systems producing multiple products are common in many industries, where products are made from several parts and/or sub-assemblies that require machining operations in first stage and assembly operations at later stage. Several scheduling techniques are proposed in the literature for such manufacturing system to develop near optimal schedule. A disruption in the manufacturing necessitates adjusting previously planned schedule which is known as real-time scheduling. This paper presents a comparative evaluation of different scheduling methods proposed by different investigators for dealing such situations. The literature indicates that real-time scheduling of manufacturing system with machining and assembly operations is hardly attempted. The paper offers a framework for developing rescheduling methodologies for such manufacturing situations.     

Performance measurement for a manufacturing system based on quality,cost and time

Product quality, manufacturing cost and manufacturing time are three of the major concerns in a manufacturing system. This study proposes a product capability index to evaluate the quality of a multi-process product and addresses the relationship between process yield and the product capability index. In addition, this paper develops a time–cost index to assess manufacturing cost and manufacturing time. The quality index and time–cost index are simultaneously used to monitor product quality and manufacturing time on a quality and time–cost analysis chart. The quality and time–cost analysis chart, providing accurate information on the quality status and time–cost status for each process, helps to initiate, effectively and efficiently, quality improvement plans to elevate product quality and manufacturing time and manufacturing cost control for a manufacturing system.     

On-line optimization of quality in a manufacturing system

One of the major obstacles contributing to the cost, time and efficiency of improving the quality output of manufacturing systems is the propagation of defectives or errors through the system. Design of Experiments (DoE), the response surface plot and a Neural Network Metamodel (NNM) can be used automatically to detect the interrelationship of the system without the need for complex analytical tools and costly intervention. A case study is conducted here to demonstrate the capability of DoE, the response surface plot and NNM in building a decisionsupport model for achieving six-sigma quality for a manufacturing system with a significant shift in the mean number of defectives produced. The case study is based on a discrete event simulation model of an actual manufacturing system. A response surface plot is used as an off-line decision support tool. Alternatively, a grid search method implemented on the NNM can be used as an on-line decision support tool in the manufacturing system with a real-time database system.     

Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system

In this article, scheduling problem of a space-constrained AGV-based prefabricated bathroom units (PBU) manufacturing system is addressed. Space becomes a key resource to this manufacturing system because a very large space is required to accommodate the settling units as well as the queues. Although line balancing helps to reduce the queues, the system is still prone to deadlock due to limited space. Hence, in order to prevent deadlock situations, the production start times of PBUs have to be controlled. A genetic algorithm is proposed with the objective to decide operation for each workstation and to choose a start time for each PBU. The project duration is minimised while satisfying precedence relations and resource availabilities. A rule-based simulation approach is used to estimate the fitness value of every GA chromosomes. At last, the experiment based on data from an industrial project shows that the proposed algorithm has the potential to guide the real practice.     

Condition-based maintenance for a system subject to a non-homogeneous wear process with a wear rate transition

The aim of this paper is to propose an adaptive maintenance model for a gradually deteriorating system. The system considered initially deteriorates with a nominal deterioration rate and at an unknown time the system's deterioration rate changes and the new deterioration rate is a time-dependent function. To deal with the transition of mode of deterioration in the framework of the maintenance decision rule an adequate online change detection algorithm is used. The maintenance decision rule is chosen in order to minimise the total maintenance cost including the cost of unavailability. The main result of this paper is to point out the interest of using a detection algorithm and hence the appreciation of a decision rule which takes into account transitions in the deterioration rate.     

Time-based replacement policies for a fault tolerant system subject to degradation and two types of shocks

A single component nonrepairable system suffering from both an internal stochastic degradation process and external random shocks is investigated in this paper. More specifically, the Wiener process with a positive drift coefficient is introduced to describe the gradual deterioration and the arrival number of external shocks is counted with a nonhomogeneous Poisson process (NHPP). Meanwhile, fault tolerant design is incorporated into the stochastically deterioration system so as to protect it from shock failures to some extent and is consummately addressed via a generalized m − δ shock model. From the actual engineering point of view, external shocks are typically classified into two distinct categories in this current research, that is, a minor shock (Type I shock) increasing the damage load on current degradation level and a traumatic shock (Type II shock) resulting in system catastrophic failure immediately. The closed-form expression of system survival function is derived analytically and is viewed as the generalization of existing reliability function for systems subject to dependent and competing failure processes. Based on which, two time-based maintenance (TBM) policies including an age replacement model and a block replacement model are scheduled, where the expected long-run cost rate (ELRCR) in each model is, respectively, optimized to seek the optimal replacement interval. In the illustrative example part, a subsea blowout preventer (BOP) control system is arranged to validate the theoretical results numerically. To compare which policy is more profitable under different conditions, the relative gain on optimal maintenance cost rate of the two TBM policies is presented.     

Development of a software tool to improve performance of packaging operations through short interval scheduling

A manufacturer of precision extruded aluminum parts needed to improve productivity and scheduling in its packaging department. Because of the non‐standard, irregular nature of the department's work, this market leader chose short interval scheduling (SIS) as the solution. However, in order for SIS to be effective, the company needed to create labour and material standards for the packaging process. Personnel from the Enterprise Systems Center (ESC) at Lehigh University collaborated with the company and, using a standard methodology for process analysis and change, created those standards. Information derived from the implementation of those standards permitted ESC personnel to develop a decision support tool that could more accurately calculate the cost of the packaging and shipping operation. This tool also provided the information necessary to effectively implement SIS. The theory of SIS is described, along with a brief summary of the pertinent literature. The current system is analysed and the desired performance improvements are identified. The development of the decision support tool, the results achieved through its usage, and final conclusions are reviewed. Copyright © 2003 John Wiley & Sons, Ltd.     

A hierarchical process monitoring strategy for a serial multi-stage manufacturing system

This paper illustrates the process monitoring strategy for a multistage manufacturing facility with the aid of cluster analysis and multiple multi-block partial least squares (MBPLS) models. Traditionally, a single MBPLS model is used for monitoring multiple process and quality characteristics. However, modelling all the responses together in a single model may cause poor model fit in the events of: (i) uncorrelated response variables; and (ii) groups of response variables having high correlation amongst the variables within a group but no or negligible correlations between the groups. This paper overcomes this problem by combining cluster analysis with MBPLS through development of multiple MBPLS models. Each of the MBPLS models is used to detect out-of-control observations and a superset of the out-of-control observations is created. Two new fault diagnostic statistics for stage-wise and variable-wise contribution are developed for the superset. The developed methodology is applied to a steel making shop for monitoring. The case study results show that the proposed methodology performs better as compared to the traditionally employed single MBPLS model.     

Optimisation of integrated process planning and scheduling using a particle swarm optimisation approach

Traditionally, process planning and scheduling are two independent essential functions in a job shop manufacturing environment. In this paper, a unified representation model for integrated process planning and scheduling (IPPS) has been developed. Based on this model, a modern evolutionary algorithm, i.e. the particle swarm optimisation (PSO) algorithm has been employed to optimise the IPPS problem. To explore the search space comprehensively, and to avoid being trapped into local optima, the PSO algorithm has been enhanced with new operators to improve its performance and different criteria, such as makespan, total job tardiness and balanced level of machine utilisation, have been used to evaluate the job performance. To improve the flexibility and agility, a re-planning method has been developed to address the conditions of machine breakdown and new order arrival. Case studies have been used to a verify the performance and efficiency of the modified PSO algorithm under different criteria. A comparison has been made between the result of the modified PSO algorithm and those of the genetic algorithm (GA) and the simulated annealing (SA) algorithm respectively, and different characteristics of the three algorithms are indicated. Case studies show that the developed PSO can generate satisfactory results in optimising the IPPS problem.     

Cost minimization for periodic maintenance policy of a system subject to slow degradation

This paper considers a repairable system which undergoes preventive maintenance (PM) periodically and is minimally repaired at each failure. Most preventive maintenance models assume that the system improves at each PM so that the hazard rate is reduced to that of a new system or to some specified level. In this paper, we consider the situation where each PM relieves stress temporarily and hence slows the rate of system degradation, while the hazard rate of the system remains monotonically increasing. The optimal number and period for the periodic PM that minimize the expected cost rate per unit time over an infinite time span are obtained. We also consider the case when the minimal repair cost varies with time. Explicit solutions for the optimal periodic PM are given for the Weibull distribution case.     

Online maintenance policy for a deteriorating system with random change of mode

Most of maintenance policies proposed in the literature for gradually deteriorating systems, consider a stationary deterioration process. This paper is an attempt to take into account stochastically deteriorating systems which are subject to a sudden change in their degradation process. A technical device subject to gradual degradation is considered. It is assumed that the level of degradation can be resumed by a single scalar variable. An online maintenance decision rule is proposed, which makes it possible to take into account in real time the online information available on the operating mode of the system as well as its actual deterioration level. We show the efficiency of considering online decision rules for maintenance with respect to traditional maintenance policies based on a static alarm threshold. Numerical simulations are given, to assess and optimize the performance of the maintained system from its asymptotic unavailability point of view. It is compared to the results obtained with classical control-limit maintenance policies.     

解读GB/T28863-2012《商品质量监督抽样检验程序具有先验质量信息的情形》标准

新颁布的GB/T 28863-2012于2013年2月15日实施,专门针对流通环节商品的质量监督抽样检验程序,解决了流通环节商品的抽查成本高、监管效能较低下等问题,使监督检验结论的适用范围不再仅限于某一经营者或者某一批次不合格商品,有效提升了监管部门的抽检工作统筹管理,并有助于指导行业质量整改和提高。     

Generation of production material information for a building block and simulation of block erection for process planning and scheduling in shipbuilding

At the initial process planning and scheduling stage of a ship, the generation task of the production material information of a building block and the simulation task of the block erection have been manually performed using 2D drawings, etc. To make these tasks automatic, an accurate generation method for the production material information and a convenient simulation method for block erection using a 3D CAD model are developed in this study. For this, a 3D CAD model for a whole hull structure is generated first, and the block division method for dividing the 3D CAD model into a number of building blocks is then developed using the relationship between the hull structural parts. A generation method for the production material information for calculating the weight, etc., of a building block is developed. A simulation method for block erection is also developed using the composition and erection sequence information of erection blocks. Finally, to evaluate the developed methods, these methods are applied to corresponding processes of a deadweight 300 000-ton very large crude oil carrier. As a result, it is shown that the production material information can be accurately generated and the block erection can be conveniently simulated at the initial design stage.     

Dynamical model of total and partial pressures in a vacuum system due to intermittent desorption

The dynamical characteristics of a vacuum system in respect of pressure are critical for studying the dynamical desorption processes such as those produced by mechanically stimulated desorption in vacuum. In the present work, a mathematical model of the instant pressure in a vacuum system has been developed assuming an intermittent square-wave desorbed gas flow. In this case, the duration of the pressure transient is proposed to be used as a generalized criterion of the rate of the desorbed gas flow and, consequently, of the instant pressure behaviour. The dependences of the transient duration on the pumping speed, system volume, molar mass of the desorbed gas as well as on the period and the on-off ratio of the desorption process have been revealed. The developed model made no assumptions on the physical nature of the gas source, i.e. desorption, leaking, etc., and can be used for different applications.