Reducing energy consumption in serial production lines with Bernoulli reliability machines

This paper is devoted to developing an integrated model to minimise energy consumption while maintaining desired productivity in Bernoulli serial lines with unreliable machines and finite buffers. For small systems, such as three- and four-machine lines with small buffers, exact analysis to optimally allocate production capacity is introduced. For medium size systems (e.g. three- and four-machine lines with larger buffers, or five-machine lines with small buffers), an aggregation procedure to evaluate line production rate is introduced. Using it, optimal allocation of machine efficiency is searched to minimise energy consumption. Insights and allocation principles are obtained through the analyses. Finally, for larger systems, a fast and accurate heuristic algorithm is presented and validated through extensive numerical experiments to obtain optimal allocation of production capacity to minimise energy consumption while maintaining desired productivity.     

Energy efficiency analysis of machine tools with periodic maintenance

Machine tools consume a large amount of energy in the production process. Effective reduction of energy consumption of the machine tool will lead to significant savings. Although substantial efforts have been devoted to reducing energy consumption of the machine tool through upgrading the equipment or improving the manufacturing process, the study of energy efficiency improvement through effective maintenance operations scheduling has received significantly less attention. Power consumption usually increases as the machine tool deteriorates in most mechanical manufacturing environments. In this paper, we develop a discrete-time, discrete-state homogeneous Markov chain of the deteriorating machine tool based on energy efficiency. To evaluate the energy performance and productivity performance of the machine tool with periodic maintenance, analytical models of average energy efficiency and average productivity are developed based on renewal reward theorem. The effects of some parameters on the average energy efficiency are analysed through a numerical example, and the trade-off between energy efficiency and productivity is discussed.     

Formation of independent manufacturing cells with the consideration of multiple identical machines

Cellular manufacturing is a manufacturing philosophy with the goal to produce low-medium volume products with high variety, while maintaining the high productivity of large-scale production. It is recognised as one of the most powerful management innovations in job-shop and batch production. Among the problems of designing a cellular manufacturing system, cell formation is the central and foremost issue. In the present paper, we investigate the formation of independent manufacturing cells with the consideration of multiple identical machines, in which inter-cell movements are completely eliminated by allocating identical machines in different manufacturing cells. Incorporating many real-life production factors including processing time, set-up time, alternative processing routes, machine capacity, batch size and cell size, we formulate a bi-objective mathematical model to minimise workload imbalance among manufacturing cells. Then, a genetic algorithm based on non-dominated sorting genetic algorithm II is developed to solve it. The computational results of numerical examples and the comparison analysis validated the performance of the proposed algorithm.     

A methodology for determining auxiliary and value-added electricity in manufacturing machines

A methodology was developed that accurately and flexibly determines the auxiliary (AU) and value-added electricity in manufacturing operations. A tool was developed for production engineers which allows for the verification of machine efficiency in relation to their energy consumption. Historical production and electricity consumption data were collected for a period of three months from four different machines in a value stream at a manufacturing facility. The data were examined using a methodology based on statistical analysis of the historical data collected and were verified using heuristic machines profiles. Results showed AU electricity consumption varied between 10 and 26% per machine. When weekend data (non-productive periods) were excluded from calculations, AU electricity consumption reduced. Past work focuses on optimising single machine, and the quantification of wasted electricity is not always clear. This research work can be applied to one or more machines, and to single or multiple products passing through the same machine. It places particular attention to AU electricity since potential energy and cost reduction of up to 20% could be achieved. Hence, this work can aid in developing key performance indicators to measure energy usage in manufacturing operations, particularly focused towards reducing AU electricity consumption.     

Integrated quality and quantity modeling of a production line

During the past three decades, the success of the Toyota Production System has spurred much research in manufacturing systems engineering. Productivity and quality have been extensively studied, but there is little research in their intersection. The goal of this paper is to analyze how production system design, quality, and productivity are inter-related in small production systems. We develop a new Markov process model for machines with both quality and operational failures, and we identify important differences between types of quality failures. We also develop models for two-machine systems, with infinite buffers, buffers of size zero, and finite buffers. We calculate total production rate, effective production rate (ie, the production rate of good parts), and yield. Numerical studies using these models show that when the first machine has quality failures and the inspection occurs only at the second machine, there are cases in which the effective production rate increases as buffer sizes increase, and there are cases in which the effective production rate decreases for larger buffers. We propose extensions to larger systems. Correspondence to: Stanley B. GershwinWe are grateful for support from the Singapore-MIT Alliance, the General Motors Research and Development Center, and PSA Peugeot-Citroën.     

Event-driven model of unreliable production lines with storage

We have developed an event-driven algorithm for simulating a factory production line with storage. Using this algorithm a production line, with an arbitrary number of machines each processing items at different rates and with buffers of any size, can be modelled efficiently. The algorithm is based on computing the time to the next event for each buffer and machine, where the events are: a buffer becomes full, a buffer becomes empty, a machine fails and a machine is repaired. By collapsing the production line to exclude empty buffers that stay empty and full buffers that stay full, piece-by-piece computation is avoided. Computation time is reduced further by updating a buffer only when the input or output rate of that buffer changes or when the state of that buffer changes. The implementation of this model is compared to a piece-by-piece simulator.     

Availability and throughput of unreliable,unbuffered production lines with non-homogeneous deterministic processing times

This paper studies production lines composed of several serial machines which are subject to random operation-dependent failures. The production lines have no intermediate buffers between adjacent machines. Machines have different deterministic processing times. The purpose of this paper is to propose analytical models to assess steady-state availability and throughput of such lines. Thousands of production line configurations have been experimented to compare the performance of the proposed approach to approximate existing techniques. A general simulation model was developed and statistical tests carried out to prove that the proposed approach is exact and robust to model unreliable, unbuffered, and non-homogeneous production lines.     

Performance analysis for serial production lines with Bernoulli Machines and Real-time WIP-based Machine switch-on/off control

In recent years, achieving high energy efficiency has become one of the primary goals in manufacturing, along with maintaining high productivity and quality. In many manufacturing systems, it is sometimes possible to temporarily switch off a machine to reserve energy, and switch it back on when a certain condition is met. Indeed, production control-based shop floor continuous improvement is recognised as one of the most cost-effective ways to achieve energy-efficient production. In this paper, we study serial production lines with Bernoulli machines and finite capacity buffers and assume that some of the machines in the line can be switched on and off during the production process according to a state-based feedback control policy. Mathematical models for the system under consideration are derived and analytical methods are developed for calculating the system performance measures during transients. Specifically, exact Markovian analysis is used for two- and three-machine lines in which the switch-on/off operations of only one machine is considered. For longer lines, the switch-on/off operations of multiple machines are considered and an aggregation-based approximation approach is applied to evaluate the system performance measures. Numerical experiments show that the method developed can be used to efficiently calculate the system’s performance with high accuracy.     

Effect of maintenance policies on the just-in-time production system

Using simulation, experimental design, and regression analysis, mathematical models are developed here to describe the effect that maintenance policy, machine unreliability, processing time variability, ratio of preventive maintenance time to processing time, ratio of minimal repair time to preventive maintenance time, and production line size have on various measures of performance, namely total production line output and production line variability of the just-in-time production system. The analysis of the data shows that under different situations, different maintenance policies do not have the same effect on the production line performance. The following conclusions were obtained; when the number of production machines is low (five machines or less), and/or when the ratio of minimal repair time to preventive maintenance time is high, maintenance policy III leads to a higher performance than maintenance policy II. Otherwise maintenance policy II, which is more sensitive to the change of the ratio of minimal repair time to preventive maintenance time, leads to a higher performance. The results of the study can be utilized in choosing a maintenance policy as a function of the production process parameters. Once a policy is chosen, the practitioner can select the most important factors to control under that policy in order to minimize the machine idle time, maximize the production process reliability, improve productivity, and therefore increase the production line performance.     

Optimal composition of number and size of machines in a multi-stage make-to-order system with due dates

We develop an optimisation model to minimise costs for work-in-process (WIP), finished goods inventory (FGI), backorders, and capacity for a multi-stage production system applying a work-ahead window work release policy. Customers arrive to a make-to-order production system and have stochastic due dates. The parameters to optimise are the capacity invested at each stage, consisting of the number of machines and the processing rate (defined by a set of possible processing rates), as well as the work-ahead window. An optimality condition is provided showing when it is optimal to invest into a single machine at each stage if processing rates are continuous decision variables. The optimality of increasing capacity towards the customer end of the production line is proven under certain conditions. For a special case consisting of two stages with M/M/s queues with exponentially distributed customer required lead time, explicit expressions for WIP, FGI and backorders are developed. A set of numerical examples illustrates the influence of predefined processing rates on the optimal number and selection of machines. A simple solution heuristic for the problem with a predefined set of processing rates is proposed and its performance is shown in a numerical example. Additionally, the influence of uncertain input rates into the production system is discussed.     

An optimal integrated lot sizing and maintenance strategy for multi-machines system with energy consumption

This paper proposes an integrated model for multi-machines dynamic lot sizing aiming to produce a single item, considering the energy consumption during the production horizon. The objective is to find, firstly, the optimal lot size as well as the number of machines that satisfy a random demand under given service level and secondly, maintenance plan depended to production planning to minimise the total production, energy and maintenance costs. In fact, the problem of energy consumption is one of the most evoked topics especially with the decision of many governments to reduce theirs (For example France is willing to reduce the total consumption by 20% by 2020). The keys of this study are to consider, firstly, the correlation between the forecasting of demand, the variation of the working machines as well as their production rates under energy constraint and secondly the correlation between the production cadences and the maintenance strategy of all machines.     

面向医疗器械企业灭菌工艺的不同容量平行机批调度

针对医疗器械企业灭菌工艺生产过程的调度问题,提出面向灭菌工艺的不同容量平行机批调度方法,建立以最小化总延迟时长、最小化总加工能耗和最大化灭菌柜装载率为目标的不同容量平行机批调度模型。并针对模型的求解提出一种改进的NSGA-III算法(Improved NSGA-III,INSGA-III)。为了获得更高质量的批调度解,采用EDT+MLC启发式规则生成INSGA-III初始种群,并设计一种局部搜索策略以改进算法迭代后期的搜索能力。最后,通过算例仿真与传统调度方法进行对比分析,验证了该模型和算法的有效性和可行性。结果表明,该模型和算法较传统调度方法有明显的优势,可为医疗企业实际生产调度提供新思路。     

Applying the network flow model to evaluate an FMC's throughput

An increasingly competitive environment and the changing customers' preference have forced manufacturers to find ways to increase productivity. The cellular manufacturing system has proved to be an alternative for improving manufacturing efficiency and increasing productivity. A major problem in implementing an FMC is how to evaluate its total throughput efficiently. In this paper, we apply a network flow model to select different machines in an FMC. This network flow model can be used in a processing environment with multiple available routings and obtain the maximum total throughput. In addition, two numerical examples are demonstrated to illustrate the use of this model. The results show that the network flow model established in this paper provides a simple and powerful tool when evaluating different machine configurations with limited information available. That is, only the operating routings and operating time are required when using the network flow model.     

Modern mill technology and centralised processing system,an alternative for improving performance of palm oil mills in Abia State,Nigeria

An assessment of palm fruit processing technologies in Abia State palm oil industry was carried out in this study. About 95% of the mills were in the small scale category with capacities in the range 0.2–3.0 t/hr. Majority (80–90%) of the mills still utilized local drums for sterilisation of fruit and clarification of oil. Palm fruit digestion and oil extraction operations have been mechanised to some extent with about 90% of the mills having one device or the other to handle the operations. Hand-operated screw press was predominant (80%) in most of the mill as a device for palm oil extraction. Fruit stripping was manually carried out. Nut/fibre separation by mechanical method is adopted by small group (40%) of the mills and 90% of the mills utilize nut cracker to crack their nuts. Most of the machines being utilized are sourced locally. Maintenance of the machines was being carried out mainly when they develop faults. More than 50% of the mills have abandoned one machine or the other with breakdown of machines being the predominant reason. Most of the mills sourced fruit by purchase or served as processing centre. The extraction rate of the mills was very low and was in the range of 7–13%. Cost of production was very high when compared with other West African palm oil producing countries. Introduction of a large scale mill utilising modern technology (and centralised processing system) in form of Public Private Partnership is being proposed. Such system will have to be backed up a palm oil act as well as adequate mobilization of the farmers in order to facilitate the adoption of the system by farmers. A modern mill of 5 t/hr capacity is being planned to serve a group of farmers in a catchment area as a model. This system will make available prompt returns to the farmers to strengthen their palm fruit production capacity and guarantee high quality oil that can be exported.     

Transient behavior of serial production lines with Bernoulli machines

The steady-state performance of production systems with unreliable machines has been analyzed extensively during the last 50 years. In contrast, the transient behavior of these systems remains practically unexplored. Transient characteristics, however, may have significant manufacturing implications. Indeed, if, for example, transients are sluggish and the steady state is reached only after a relatively long settling time, the production system may lose some of its throughput, thus leading to a lower efficiency. This paper is devoted to analytical and numerical investigation of the transient behavior of serial production lines with machines having the Bernoulli reliability model. The transients of the states (i.e., the probabilities of buffer occupancy) are described by the Second Largest Eigenvalue (SLE) of the transition matrix of the associated Markov chain. The transients of the outputs (i.e., production rate, PR, and work-in-process, WIP) are characterized by both the SLE and Pre-Exponential Factors (PEF). We study SLE and PEF as functions of machine efficiency, buffer capacity and the number of machines in the system. In addition, we analyze the settling times of PR and WIP and show that the former is often much shorter than the latter. Finally, we investigate production losses due to transients and show that they may be significant in serial lines with relatively large buffers and many machines. To avoid these losses, it is suggested that all buffers initially be half full. For two- and three-machine lines these analyzes are carried out analytically; longer lines are investigated by simulations.     

Production rate control of an unreliable manufacturing cell with adjustable capacity

This article addresses the production control problem of an adjustable capacity unreliable manufacturing cell responding to a single product type demand. The manufacturing cell is composed of an unreliable machine, called the ‘central machine’. Due to availability fluctuations, the central machine may fall short of meeting the long-term demand rate. In order to quickly adjust the production capacity and thus meet the demand, a reserve machine is called upon in support if the finished product inventory level drops below a specific threshold. Such a machine involves higher production costs compared with the central one. This article aims to determine the optimal production control policy for the involved machines in order to minimise production, inventory and backlog costs over an infinite horizon. This article proposes a continuous dynamic programming formulation of the problem and adopted a numerical scheme to solve the optimality conditions equations. The optimal production policy is shown to be described by a state dependent hedging point policy (SDHPP). To determine the optimal control policy parameters, an experimental approach based on design of experiments, simulation modelling, and response surface methodology is proposed. Several sensitivity analyses have been carried out and have shown the robust behaviour of the developed policy facing expected variations of the system parameters. The results also show that the proposed SDHPP policy outperforms classical stand-by and parallel machines based control policies. The usefulness of the proposed approach is outlined for more complex situations where the system must deal with non-exponential failure and repair time distributions.     

Machine frigorifique à absorption (eau-ammoniac) fonctionnant avec des capteurs plans sur le site de Rabat

Two-stage absorption refrigerating machines driven by solar energy have been studied for cooling applications in Morocco. A simulation program allowing the calculation of the efficiency, cooling effect and dynamic behaviour of a complete installation, including solar collectors, absorption machines and heat storage has been established. This takes into account the real efficiency of each element of the installation and a parametric study of various machine configurations has been made. The two-stage absorption machine working with the fluid pair NH₃---H₂O, with two desorbers in parallel but without a rectifying column, has been shown to be the best choice for use with flat plate solar collectors. The optimum working conditions of the machine have been determined using the hourly radiation and climatic data for the city of Rabat, Morocco. In order to ensure the continuous production of cold, the behaviour of an installation to which energy storage on the warm and cold sides have been added has been determined.     

Capacity planning of serial and batch machines with capability constraints for wafer fabrication plants

Capacity planning is crucial to the investment and performance of wafer fabs. This research proposes a practical procedure to calculate the required number of machines with serial and batch processing characteristics, respectively. Several formulae are first presented. Five heuristic algorithms are then proposed to determine the lower bound, the upper bound, and the near-optimal of the number of machines of the type with capability constraint. Data from real foundry fabs are used in a case study to determine the required number of 64 types of equipment and to evaluate the performance of the proposed procedure. The algorithm using the best ratio of production efficiency and equipment cost to select the machine type with capability constraint results in the least required number of machines, the highest machine utilisation, and the lowest equipment investment. An AutoSched AP simulation model is used to evaluate if a wafer fab using the calculated number of machines of each type can result in a preset monthly output rate. Simulation results indicate that the proposed procedure can quickly and accurately calculate the required number of machines leading to the required monthly production target. Fab managers can use this tool to conduct what-if analysis for equipment investment alternatives.     

Lot Streaming Flow Shop with a Heterogeneous Machine

Abstract

It is possible to obtain greater productivity of a production system by overlapping the operations required to process a manufacturing order. This methodology, known as lot streaming, requires dividing the production order (lot) into smaller sublots. In this article, we study production systems that include machines that operate in batch mode (processing a group of units at the same time) and single processing machines (processing one unit at a time) arranged in a flow shop configuration, that is all jobs must go through the same production stages in the same order. The obtained results show that addressing the problem with consistent sublots (a common sublot size used for the whole process) is inefficient. On the other hand, addressing the problem considering the sizing of sublots for each machine (variable sublots) greatly improves the quality of the solution but is computationally intensive (limiting the size of the problem that can be solved). Therefore, a decomposition procedure is proposed on the decision of sublots sizing. This procedure greatly improves the solution obtained using consistent sublots and does so with lower computational requirements than the variable sublots approach.     

Repair policies for additively degrading machines

This paper describes a method for determining repair policies for machines whose output degrades additively over time. The novelty of the models is that they consider both the state of the machines as well as the state of the repair facility when making repair decisions. The objective in the models is to maximize long-run production. In one model, we approximate the queue waiting time by a geometric random variable, while in the second model we approximate the waiting time by a sequence of geometric random variables (with different means). We show that as the average repair queue increases, the decision to repair must be made earlier. In addition, we show empirically that the simple geometric waiting time approximation becomes less accurate as the queue length increases and that the approximation understates the expected long-run output of the machine. A plastic moulding facility is used to motivate the problem. Computational results using industry supplied data are presented. The results indicate that substantial (10-20%) productivity improvement can be realized using the derived repair policies instead of policies that do not consider the repair queue.