Serial production lines with geometric machines and finite production runs: performance analysis and system-theoretic properties

A production run is typically referred to as a group of identical goods that is produced by a particular manufacturing process. In many discrete manufacturing practices, the manufacturing activity is carried out by deploying a series of production runs of different products according to customer orders. If the volume of a production run is relatively small and process changeovers are necessary, the production system operates partially (or entirely) in the transient regime, especially at the beginning and near the end of a production run. In this case, the traditional steady-state analysis approach may become inapplicable. In this paper, we consider finite production run-based manufacturing in serial lines with machines obeying the geometric reliability model and buffers having finite capacity. Exact Markovian analysis is first used to derive the closed-form formulae to calculate the transient performance of the production line during a production run as well as the distribution, mean, and standard deviation of its completion time in one- and two-machine lines. For multi-machine lines, an aggregation-based approach is proposed to approximate the system performance measures with high accuracy and computational efficiency. In addition, system-theoretic properties of production run completion time with respect to machine and buffer parameters are discussed.     

Modeling of machine failures in a flexible manufacturing cell with two machines served by a robot

In this study, a stochastic model is developed to analyze performance measures of a flexible manufacturing cell (FMC) under different operational conditions, including machine failures and repairs. The FMC consists of two machines served by a robot for loading and loading purposes, and a pallet handling system. The model is based on Markov processes and determines closed-form solutions for the probabilities of system states that are used to calculate system performance measures, such as production output rate and utilizations of system components under different parametric conditions and equipment failures and repairs.     

Improving energy efficiency in Bernoulli serial lines: an integrated model

In this paper, we present an integrated model of both productivity and energy consumptions in serial production lines with two machines. Bernoulli reliability is assumed for both machines and the capacity of the buffer is finite. The energy consumption of each machine includes the energy required to set up the machine until it is ready for processing, and the additional energy needed to carry out the processing operation to make the product. The former is typically fixed for a specific manufacturing process, while the latter is proportional to the processing rate. The objective of the model is to minimise energy consumption, while maintaining the desired production rate. Specifically, analytical investigation has been carried out to discover the conditions that energy consumption can be minimised with and without the constraints of workforce or machine processing capability. Optimal allocations of them under different scenarios have been derived. Insights for reducing energy consumption while still ensuring desired productivity have been obtained.     

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.     

Analytical Solution of the serial Bernoulli production line steady-state performance and its application in the shipbuilding process

The modern shipbuilding industry is faced with numerous challenges urging abiding improvement of the shipbuilding process and its management. Such a demanding problem is usually approached using complex production management models involving large data basis handling. The same problem can be solved using simpler, intuitive and mathematically transparent models developed within production system engineering. For these purposes, the analytical solution of the serial Bernoulli production line steady-state performance involving an arbitrary number of machines and buffers of arbitrary occupancy is developed based on Markov chain approach and eigenvalue problem including formulation of the generalised transition matrix as a key novelty. Performance measures in case of general serial Bernoulli production line are developed and the theory is validated using serial Bernoulli lines composed of two, three, four and five machines. The obtained results are compared to those determined using a semi-analytical approach. In order to further demonstrate the applicability of the developed theory, performance measure analysis is performed in cases of longer lines composed of 6, 7, 8, 9 and 10 machines with non-equal buffer capacities. Application of the developed procedure in the analysis of the shipbuilding process is illustrated in a case of the plate prefabrication line usually placed in each shipyard.     

卷包机组设备效率评价指标体系的设计与实现

目的 针对烟草行业常见设备卷包机组,提出一种结合OEE的设备效率评价体系,实现对卷包机组设备运行状态的精确、实时、具体的反映.方法 通过分析离散制造与连续制造的差异,在传统离散制造OEE方法基础上,针对连续生产进行适应性改进,提出一套针对卷包机组的设备效率评价指标;在此基础上,通过分析卷包机组各运行单元结构特点,提出一套实时采集设备状态数据与动态分析效率状态的卷包机组设备效率评价体系.结果 将此体系部署于湖北中烟某车间6台卷包机上6个月进行实验验证,结果显示在该体系的支持下,设备净效能平均同比增长7.72％,证明本效率评价结果可以精准、全面、实时地反映设备运行情况和状态背后的影响因素,有助于提升卷烟机组设备效率.结论 文中提出的卷包机组设备效率评价指标体系使用户可以针对性、快速地调整设备运行状态,实现了精准管理,提高了生产作业效率,具有实际的推广价值.     

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.     

Product quality inspection in Bernoulli lines: analysis,bottlenecks, and design

This paper is devoted to serial production lines consisting of producing and inspection machines that obey the Bernoulli reliability and Bernoulli quality models. Such production lines are encountered in automotive assembly and painting operations where the downtime is relatively short and the defects are due to uncorrelated random events. For these systems, this paper develops analytical methods for performance analysis, bottleneck identification, and design. In addition, insights into the nature of bottlenecks in such systems are provided, and an empirical rule for placing an inspection machine that maximises the production rate of non-defectives is formulated.     

An agent-based negotiation approach to integrate process planning and scheduling

This paper presents the development of an agent-based negotiation approach to integrate process planning and scheduling (IPPS) in a job shop kind of flexible manufacturing environment. The agent-based system comprises two types of agents, part agents and machine agents, to represent parts and machines respectively. For each part, all feasible manufacturing processes and routings are recorded as alternative process plans. Similarly, alternative machines for an operation are also considered. With regard to the scheduling requirements and the alternative process plans of a part, the proposed agent-based IPPS system aims to specify the process routing and to assign the manufacturing resources effectively. To establish task allocations, the part and machine agents have to engage in bidding. Bids are evaluated in accordance with a currency function which considers an agent's multi-objectives and IPPS parameters. A negotiation protocol is developed for negotiations between the part agents and the machine agents. The protocol is modified from the contract net protocol to cater for the multiple-task and many-to-many negotiations in this paper. An agent-based framework is established to simulate the proposed IPPS approach. Experiments are conducted to evaluate the performance of the proposed system. The performance measures, including makespan and flowtime, are compared with those of a search technique based on a co-evolutionary algorithm.     

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.     

Designing integrated cellular manufacturing systems with tactical decisions

In this paper, we aim to design cellular manufacturing systems that optimize the performance of a manufacturing system subject to the optimization aspects of production planning. Consequently, the demand for each part – one of the production planning features – plays a vital role in determining the part families and the formation of machine cells in each period. In our study, holding and backorder costs follow a probabilistic structure, and they are described by a set of stochastic scenarios. In this model, five objective functions are employed: one of them minimizes the expected total holding and backorder costs in order to evaluate the risk in the model. The aim of this model is to select and optimize the assignment of parts and machines to different cells as well as the number of each produced part in each period. A new heuristic algorithm based on the optimization method is established to yield the best solution for this complicated mathematical formulation. Further, the performance of the proposed algorithm is verified using certain test problems in which the obtained results are compared with those obtained using the branch-and-bound algorithm and heuristic procedures.     

Robust production control policy for a multiple machines and multiple product-types manufacturing system with inventory inaccuracy

Inventory inaccuracy often exists in manufacturing systems, which has great negative impact on the performance of production control, e.g. very high work-in-process holding cost or backlog penalty. To hedge against inventory inaccuracy, the robust production control problems will be investigated for a multiple machines and multiple product-types manufacturing system with uncertain production capacity. The objective of our problem is to minimise the average production cost. To solve this problem, a robust production control policy is developed, which is insensitive to the inventory record errors, and whose robustness is better than the traditional hedging point policy for optimal production control. Finally, numerical experiments are conducted to examine the performance of the proposed robust production control policy against inventory inaccuracy. Based on the experimental results, the conditions of applying the proposed policy are also obtained.     

Exact analysis of a discrete material three-station one-buffer merge system with unreliable machines

In this paper, a model of a discrete material flow line consisting of three unreliable machines and one buffer of limited capacity is analysed. A similar system, but with continuous flow of material was examined by Helber and Mehrtens (2001) and Tan (2001). In our system it is assumed that the buffer has two immediate preceding machines, performing the same operations and one immediate succeeding machine that receives material from the buffer. For the case where the buffer reaches its own capacity, one of the two preceding machines has priority over the other to dispose its processed part into the buffer. Processing times are assumed to be deterministic and identical for all machines and are taken as the time unit. Geometrically distributed operation dependent failures at the machines are assumed. All possible transition equations for the examined model are derived and a recursive algorithm that generates the transition matrix for any value N of the storage level is developed. Once the transition matrix is known the performance measures of the model under consideration can be easily evaluated. This model may be used as a building block in a decomposition method to evaluate large production systems with split/merge operations (for example, flow lines with quality inspections and rework loops).     

Availability consideration in the optimal selection of multiple-aspect RMS configurations

Machine availability has a profound influence on the performance of manufacturing systems. This paper extends a model for optimizing reconfigurable manufacturing systems (RMS) configurations with multiple-aspects to incorporate the effect of machine availability using the universal generating function (UGF). Two powerful meta-heuristic optimization techniques, namely genetic algorithms (GAs) and tabu search (TS), are used for optimizing the capital cost and system availability of the RMS configurations. The optimized configurations can handle multiple-parts and their structure is that of flow lines allowing paralleling of identical machines in each production stage. The various aspects considered in the RMS configurations include arrangement of machines, equipment selection and assignment of operations. A case study is presented and implementation of the optimization model is carried out using MATLAB software. The results of using both GAs and TS to solve the problem are then reported and compared for validation. Analysis of different cases of availability consideration including infinite and no buffer capacity is performed and results are compared to those obtained when machine availability is not considered. It has been shown that considering availability affects the optimal configuration selection and increases the required equipment. This increases the costs of the near-optimal configurations obtained especially in the case without buffers. The presented model can support the manufacturing systems configuration selection decisions at both the initial design and reconfiguration stages.     

Simulation-based performance analysis and optimization of electronics assembly equipment

Due to the high degree of automation in modern printed circuit board (PCB) assembly, production planning and scheduling in this industry relies heavily on the accuracy of the underlying models of the automated machinery. In this paper, the derivation of such mathematical models is exemplified for one of the most wide-spread machine types (the so-called chip shooter). Moreover, a simulation system for practical use in the electronics assembly is presented which incorporates various types of assembly machines. It serves as a tactical production planning aid as well as a test field for the analysis of the kinematic processes of PCB assembly machines. Such simulation, tailored to the specifics of a production environment, gives reliable estimates of the achievable production volume. Considerable deviations between the performance figures provided by the machine supplier and the actual result can thus be explained, and potential assembly system configurations be compared by drawing on reliable measures. Since the equipment is modelled at a level which takes precise account of its specific kinematics, a detailed analysis of the operations of the individual machine can also be performed revealing potential bottlenecks in its design. These insights are used to optimize machine design and control. Methods based on graph theory as well as on modern numerical search algorithms have been developed for the latter purpose. They lead to considerable performance improvements.     

Optimal production control: analytical solution for the limit cycles

The paper analyzes a manufacturing system with tandem machines producing one part type. The system is periodically stopped for maintenance. The objective is to determine machine production rates so that the inventory and backlog-related expenses could be minimized. We show only a few so-called restricting machines need to be considered. A numerical example is used to demonstrate the solution approach proposed in the paper.     

Throughput analysis of production systems: recent advances and future topics

Throughput analysis is important for the design, operation and management of production systems. A substantial amount of research has been devoted to developing analytical methods to estimate the throughput of production systems with unreliable machines and finite buffers. In this paper we summarise the recent studies in this area. In addition to the performance evaluation of serial lines, approximation methods for more complex systems, such as assembly/disassembly systems, parallel lines, split and merge, closed-loop systems, etc., are discussed. Moreover, we propose future research topics from the automotive manufacturing systems perspective.     

Modeling and Analysis of Assembly Systems with Unreliable Machines and Finite Buffers

An assembly line is a tree-structured manufacturing system in which some machines perform assembly operations. In this paper, we consider assembly lines with the following features: every operation is performed in a fixed amount of time, machines are unreliable, and buffers have finite capacity. Usually, the times to failures of machines are much larger than the processing times. This allows us to approximate the behavior of these systems by a continuous flow model. The behavior of this model is then analyzed using a decomposition technique which is an extension of an earlier technique proposed in the case of transfer lines. An efficient algorithm for calculating performance measures such as production rate and average buffer levels is derived. Experimental results are provided showing mat this approximate method is quite accurate.     

Lockout/tagout and optimal production control policies in failure-prone non-homogenous transfer lines with passive redundancy

This paper considers a production problem for a transfer line subject to random failures and repairs, and differs from other studies on transfer lines. It considers a manufacturing system consisting of three machines (two machines with passive redundancy, and one in series with the previous ones) producing one part type. The control problem is subject to non-negative constraints on work-in-process (WIP). The decision variables are the production rates of two main machines and a standby machine, and influence the WIP levels, the inventory levels and the system's capacity, which is assumed to be described by a finite-state Markov chain. The objective of this paper is to minimise WIP and finished goods inventory costs; it also aims to respect the essential space–time during intervention on machine down, in order to minimise the possibility of the circumvention of protection devices or of the retraction of lockout/tagout procedures through a passive redundancy system. This paper therefore verifies the effect of passive redundancy on optimal stock levels. Given that an analytical or even a numerical solution of the problem is very difficult to find, and that we want to have a more realistic model for industries, we present a combined approach, which is presented based on a combination of analytical formalism, simulation modelling, design of experiments, and response surface methodology to optimise a transfer line with passive redundancy, producing one part type. The usefulness of the proposed approach is illustrated through a numerical example and a sensitivity analysis.     

制罐过程中存在的问题及改进措施

目的针对郑州X制罐厂方便桶自动生产线故障多的现象,分别从缝焊机、组合机、烘箱等环节实施改进,解决其废品率高的问题。方法首先通过现场拍照取证的方式对故障现象进行描述,其次分析故障发生的原因及危害,然后和相关技术人员进行深刻探讨,最后通过查阅相关资料,对每个故障环节提出具体的改进措施,并将其应用于方便桶自动生产线。结果该生产线在实施相应改进措施后,工废废品率从0.464%降至0.129%,为制罐业的方便桶自动生产线改善提供依据。结论制罐过程中存在的问题多源自缝焊机、组合机、烘箱等环节,企业应多从这几方面进行严格控制,采取相应的改善措施,达到降低废品率的目的。