Multi-product Manufacturing System Research Articles

Resource breakdown modelling and performance maximisation of a multiple product flexible manufacturing system

This paper models, analyses and maximises performance of a pull type multiproduct, multiline and multistage Flexible Manufacturing System (FMS) whose resources are subject to breakdown conditions. To ensure a continual supply of the finished products, under breakdown conditions, parts/materials flow through alternate routes exhibiting routing flexibility. The system is modelled through Coloured Petri Net (CPN) method and the results of the system performance are presented. The study is extended to achieve maximum performance of the system using Design of Experiment (DoE) and Response Surface Methods (RSMs).

The Impact of Guide Path Configurations on Performance of an Integrated Automated Guided Vehicle System Using Coloured Petri Net

The objective of this study is to analyse an integrated Automated Guided Vehicle System (AGVS) which is embedded in a pull type multi-product, multi-stage and multi-line flexible manufacturing system (FMS). The analysis is carried out through the development of different guide path configurations. Three guide-path configurations are developed to add flexibility gradually in the AGVS and the impact of added flexibility is studied by examining the performance of the system. The study uses coloured Petri net methodology to model the system and the simulation results lead to decrease the number of automated guided vehicles and hence the overall cost of the system.

Advanced Multiple Product Flexible Manufacturing System Modelling Using Coloured Petri Net

The objective of this study is to analyse a pull type multi-product, multi-line and multi-stage flexible manufacturing system whose resources are subject to planned and unplanned breakdown conditions. To ensure a continual supply of the finished products, under breakdown conditions, the parts/materials move through alternate routes exhibiting routing flexibility. The machine resources are flexible in this study and are capable to produce more than one item. Every machining and assembly station has been equipped with automated inspection units to ensure the quality of the products. The system is modelled through coloured Petri net method and the impact of input factors has been shown on the performance of the system.

Re-Examining the Performance of MRP and Kanban Material Control Strategies for Multi-Product Flexible Manufacturing Systems

Material control schemes can be classified as push, pull, or hybrid strategies. This article compares the performance of MRP (push) and kanban (pull) for a multi-stage, multi-product manufacturing system. Using simulation experiments we analyze system performance under different product mixes and observe that in certain environments with advance demand information kanban-based pull strategies can lead to significant inefficiencies. In these environments MRP-type push strategies yield better performance in terms of inventories and service levels. We also study the impact of design parameters such as safety lead time and safety stock policies on system performance and observe that for low and medium values of system loads, safety lead time policies yield better system performance than safety stock policies. These insights can be helpful in designing efficient MRP-type push strategies in multi-product environments.

多品種半導体生産システムにおけるレイアウトの自己組織化(ソフト人工物II)

多品種半導体生産システムにおけるレイアウトの自己組織化(ソフト人工物II)

Analysis of Optimum Batch Size in Multistage, Multifacility and Multiproduct Manufacturing Systems

In any type of manufacturing environment the most common configuration will be a multistage, multiproduct, manufacturing inventory system. An in-process inventory is inherent in any multistage manufacturing system, when the product is manufactured through several operations and stages. To satisfy demand requirements in multistage, multiproduct manufacturing systems, it is important to specify feasible production quantities, as batch sizes for each end product, over a finite time period at every stage. This paper deals with different methods for determining batch sizes in a multiproduct, multistage situation in the presence of decision support systems for maximum capacity. The mathematical model suggested by Gunasekaren is considered as the basis for comparison. A fuzzy logic model of the above has been developed to calculate the economic batch sizes such that machine hour and labour productivity constraints are not violated. Using Promodel, a simulation technique, the model was subjected to variable analysis and cost analysis and the results were compared. Case studies were conducted for validating the models for their ability to produce reliable output. MATLAB software package is used for developing the program to solve the problem by fuzzy approximation.

Multiproduct Kanban-like Control Systems

Kanban Control Systems are widely used to control the release of parts in multistage manufacturing systems operating under a pull mechanism, i.e. production of new parts is triggered based on the actual demands arriving to the output of the system. Most of the work on Kanban Control Systems deals with single-product manufacturing systems, although Kanban Control Systems have also been used in multiproduct environments. The aim is to study in detail the behaviour of Kanban Control Systems in the context of multiproduct manufacturing systems. In addition to the classical Kanban Control System, we also consider two more general Kanban-Like Control Systems known as Generalized Kanban Control System and Extended Kanban Control System. When extending these pull control mechanisms to multi-product systems, we distinguish two cases, whether kanbans are dedicated to a single part type or shared among the different part types. We provide an in-depth analysis of each of the resulting control mechanism and discuss some important issues arising from the study.

Structure of a Simulation Model for a Manufacturing System Coordinated by Production Authorization Cards

Abstract This article presents a structure of a simulation model of a multicell multiproduct manufacturing system coordinated by Production Authorization Cards (PAC system). The PAC system provides a general framework for management and control of a production process because, through the appropriate choice of parameters, it can be specialized into a wide variety of well-known production policies. The article illustrates how this complex manufacturing control strategy can be simulated using a small number of event routines. The resulting program is fast and flexible enough to be used in other studies as a performance evaluation subroutine in an overall parameter optimization.

Discounted Stochastic Fluid Programs

We consider optimal control problems for stochastic fluid models of the following type: Suppose (Zt) is a continuous-time Markov chain with finite state space. As long as Zt = z, the dynamics of the system at time t are given by a function bz(u(·)), where u is a control we have to choose. A cost rate function c is given, depending on the state and the action. We want to control the system in such a way as to minimize the expected discounted cost over an infinite horizon. We will call a problem of this type a Stochastic Fluid Program (SFP). They typically appear in production and telecommunication systems. We formulate the optimization problem as a discrete time Markov decision process and give conditions under which an optimal stationary policy exists. Furthermore, we show how to solve SFPs numerically, using Kushner's approximating Markov chain approach. Last but not least, we apply our results to a multiproduct manufacturing system without backlog.

Requirements Planning with Substitutions: Exploiting Bill-of-Materials Flexibility in Production Planning

Designing product lines with substitutable components and subassemblies permits companies to offer a broader variety of products while continuing to exploit economies of scale in production and inventory costs. Past research on models incorporating component substitutions focuses on the benefits from reduced safety-stock requirements. This paper addresses a dynamic requirements-planning problem for two-stage multi product manufacturing systems with bill-of-materials flexibility, i.e., with options to use substitute components or subassemblies produced by an upstream stage to meet demand in each period at the downstream stage. We model the problem as an integer program, and describe a dynamic-programming solution method to find the production and substitution quantities that satisfy given multi period downstream demands at minimum total setup, production, conversion, and holding cost. This methodology can serve as a module in requirements-planning systems to plan opportunistic component substitutions based on relative future demands and production costs. Computational results using real data from an aluminum-tube manufacturer show that substitution can save, on average, 8.7% of manufacturing cost. We also apply the model to random problems with a simple product structure to develop insights regarding substitution behavior and impacts.

Stability of real-time lot-scheduling and machine replacement policies with quality levels

We consider a single machine, multiproduct manufacturing system which can operate at finitely many quality levels. The quality of the machine deteriorates according to a continuous-time Markov process and the only way to improve the quality is by replacing the machine by a new one. In this framework we derive conditions for the stability of the system under a simple class of real-time scheduling/replacement policies. The stability notion that we employ is the recurrence of the total work backlog.

Batch scheduling in a multistage, multiproduct manufacturing system – an application

This paper reports the results of our collaborative work with Changde Telecommunication Equipment Company (CTEC) which produces digital transfer control systems for telephone networks. The manufacturing operations consist of two principle stages of module production and system assembly. Critical system components are produced in the module production stage where high inventories were a major managerial concern. We studied CTEC’s module production system and proposed three modifications to reduce inventories and improve system performance. The current system and the proposed modifications were simulated and compared in terms of various operational and financial criteria. The simulation was repeated in its entirety under a high level of demand due to CTEC’s anticipation of increased market share. The results, endorsed by CTEC’s management, demonstrate that significant operational and financial benefits can indeed be realized using the proposed modifications. This study provides motivation for the development of concepts and methodologies that will be useful in future theoretical and practical research.

A Multi-Level Model for Control Design of Manufacturing Systems with Unreliable Machines

Two models are used to compute optimal production rates for a multi-machines multi-product manufacturing system subject to machine failures. It is shown that both models are complementary and could be used together. The evaluation of their performances and the re-adjustment of the control design procedure is done by using simulation in a Witness environment. An example is treated to illustrate the proposed technique.

Control policies for multi-product multi-stage manufacturing systems: An experimental approach

We investigate the behaviour of a multi-product, multi-stage pull-type production/ inventory system operating under a variety of manufacturing control policies. The system consists of multiple stages in series with finite interstage buffer space and a single processor. The first stage has always sufficient amount of raw material to work on and the last stage is followed by a finite-capacity warehouse. Demand for a product follows a compound Poisson distribution. Any unsatisfied portion of the demand is backordered. The inventory level as well as the production process of each product at each stage are controlled through the use of an (R, r) continuousreview inventory control policy. A set-up is involved whenever a switch-over takes place to another product at any stage. Using a particular test case, we have evaluated various manufacturing strategies and switching policies under static as well as dynamic priority structures. We have compared the operating regimes by observing a set of performance measures such as the average inventory levels, the average backorder size, the average backorder levels, the probability of backorder and the average number of set-ups. We conclude proposing control policies for better customer service level for given scenarios.

Optimal robot operation and selection using quality and output trade-off

This paper presents a two-stage model for industrial robot operation and selection in a multi-product manufacturing system. The quality of the production process is related to robot repeatability and the output rate is related to robot speed. Robot repeatability deteriorates with increased speed. In the second stage, a one-period robot operational model maximises the expected profit of a risk-neutral decision maker, leading to optimal robot speed and production quantity decisions. Using the optimal speeds and quantities of the operational model and taking into account demand uncertainties, the first stage robot selection model is solved.

Throughput analysis in manufacturing networks

The throughput of a plant is a measure of major importance when assessing its ability to compete successfully in the market place. Managers often rely on changes in capacity (production rate) and process improvements as two major factors that impact throughput. The optimal allocation of resources to these two factors is difficult to determine without the support of appropriate mathematical models. In this paper we attempt to quantify the tradeoffs between capacity and process improvements, through variance reductions, and throughput. We consider multiproduct manufacturing systems modeled by open networks of queues and formulate the throughput characterization (TC) and variability reduction (VR) problems as nonlinear programs. These formulations are based on the decomposition approach for estimating the work-in-progress in open queueing networks. We show, by demonstrating the applicability of greedy-type heuristics for the TC and VR problems, that the overall impact of a wide variety of process improvement practices on WIP and throughput can be evaluated very efficiently.

Stability of real-time lot scheduling policies for an unreliable machine

A single-machine multiproduct manufacturing system with random breakdowns and random repair times is considered. Under a weak capacity condition on the system it is shown that the total work-in-progress (WIP) is a recurrent stochastic process. By replacing the stochastic model by a deterministic one with preventive maintenance activities scheduled on a regular basis or by strengthening the capacity condition, the boundaries of WIP and expected WIP, respectively, over time can be shown. >

Capacity planning in manufacturing networks with discrete options

We consider multiproduct manufacturing systems modeled by open networks of queues with general distributions for arrival patterns and service times. Since exact solutions are not available for measuring mean number of jobs in these systems, we rely on approximate analyses based on the decomposition approach developed, among others, by Reiser and Kobayashi [16], Kuehn [14], Shanthikumar and Buzacott [19], Whitt [29], and extensions by Bitran and Tirupati [2]. The targeting problem (TP) presented in this paper addresses capacity planning issues in multiproduct manufacturing systems. Since TP is a nonlinear integer program that is not easy to solve, we present a heuristic to obtain an approximate solution. We also provide bounds on the performance of this heuristic and illustrate our approach by means of a numerical example.

Decision architectures for production planning in multi-stage multi-product manufacturing systems

Recent trends in automated manufacturing call for hierarchical decision architectures for production planning, suitable for integration with part flow controls. Different design approaches are currently adopted for implementing production planning architectures, depending either on the objective of defining a centralized production plan for the whole manufacturing system (as in the case of MRP and OPT), or on the desire of coordinating local plans for the component work cells (as for JIT). The paper analyzes such approaches by use of a unifying mathematical formulation of the production plan optimization problem, to recognize the main features of the existing planning approaches, and compare their usefulness in different manufacturing processes.

Tradeoff Curves, Targeting and Balancing in Manufacturing Queueing Networks

In this paper, we introduce the notions of tradeoff curves, targeting and balancing in manufacturing systems to describe the relationship between variables such as work-in-process, lead-time and capacity. We consider multiproduct manufacturing systems modeled by open networks of queues and formulate the targeting (TP) and balancing (BP) problems as nonlinear programs. These formulations are based primarily on parametric decomposition methods for estimating performance measures in open queueing networks. Since TP and BP typically are hard to solve, we show that under fairly realistic conditions they can be approximated by easily solvable convex programs. We present heuristics to obtain approximate solutions to these problems and to derive tradeoff curves. We also provide bounds on the performance of the heuristics, relative to the approximation problems, and show that they are asymptotically optimal under mild conditions.