Genetic algorithm to production planning and scheduling problems for manufacturing systems

Fundamental and extended multi-objective (MO) models are designed to address earliness/tardiness production scheduling planning (ETPSP) problems with multi-process capacity balance, multi-product production and lot-size consideration. A canonical genetic algorithm (GA) approach and a prospective multi-objective GA (MOGA) approach are proposed as solutions for different practical problems. Simulation results as well as comparisons with other techniques demonstrate the effectiveness of the MOGA approach, which is a noted improvement to any of the existing techniques, and also in practice provides a new trend of integrating manufacturing resource planning (MRPII) with just-in-time (JIT) in the production planning procedure.     

Decision support systems for production scheduling tasks- Part I of a case study: Analysis and task redesign

The first three steps of a new design method for decision support systems in production scheduling tasks are applied to a large bulk terminal. The operational characteristics of the company largely correspond with those of typical semiprocess industries. The design model used consists of five steps: production analysis, task analysis, task redesign, decision support design and decision support implementation. The results of the application of the design model up to the task redesign step are described.     

Earliness/Tardiness Production Scheduling and Planning,and solutions

Earliness/Tardiness Production Planning (ETPSP) has attracted much attention in recent years. In practice, it provides an efficient way to integrate Manufacturing Resource Planning (MRP-II) Scheduling and with Just-In Time (JIT). Conventional research mainly focused on the condition of single-machine and parallel multi-machine. Capacity balance has not been considered. Some investigations of existing research on ETPSP are given in this paper. An extensive model of ETPSP with consideration of multi-process capacity balance for manufacturing systems is proposed. Two alternative solutions, key-process method and relaxation method, are both developed to solve ETPSP. Computational results identify that both methods are powerful to solve ETPSP which minimizes total earliness and tardiness penalties. Furthermore, some comparisons between these two methods and other conventional methods indicate the efficiency of the former.     

Development of a computer-aided production management course in industrial engineering curriculum

This paper describes the successful development and demonstration of an integrated computer-aided production management course which is very user-friendly and which facilitates integration of decisions. An icon-menu system that associates icons with the various decision models which were all implemented under the same environment allows students to easily integrate individual decision situations. Decisions were edited and their effect on other decisions confirmed that the hierarchical individual decisions situations in production management need to be integrated. The software developed runs on a personal computer coupled to a projection panel and overhead projector. This arrangement makes it an effective teaching facility for production management.     

A Model for Master Production Scheduling in Uncertain Environments

In uncertain environments, the master production schedule (MPS) is usually developed using a rolling schedule. When utilizing a rolling schedule, the MPS is replanned periodically and a portion of the MPS is frozen in each planning cycle. The cost performance of a rolling schedule depends on three decisions: the choice of the replanning interval (R), which determines how often the MPS should be replanned; the choice of the frozen interval (F), which determines how many periods the MPS should be frozen in each planning cycle; and the choice of the forecast window (T), which is the time interval over which the MPS is determined using newly updated forecast data. This paper uses an analytical approach to study the master production scheduling process in uncertain environments without capacity constraints, where the MPS is developed using a rolling schedule. It focuses on the choices of F, R, and T for the MPS. A conceptual framework that includes all important MPS time intervals is described. The effects of F, R, and T on system costs, which include the forecast error, MPS change, setup, and inventory holding costs, are also explored. Finally, a mathematical model for the MPS is presented. This model approximates the average system cost as a function of F, R, T, and several environmental factors. It can be used to estimate the associated system costs for any combination of F, R, and T.     

Real-time scheduling and control of one-of-a kind production

Due to the great diversity of product types in one-of-a-kind production (OKP), the production scheduling and control in OKP is much more difficult than production scheduling and control of other production systems, e.g. mass production and batch production. Hence, the production efficiency in OKP companies is relatively lower. To improve productivity in OKP, a dynamic hierarchy production control system is presented. Using this control structure, a production system in an OKP company can be flexibly organized or re-organized according to the structure of a customized product (or an OKP product). Production synchronizing and scheduling algorithms for OKP shop floor production control are presented. Using these algorithms, a cybernetic model can be developed for shop floor control in OKP. The algorithms are applied to two alternate production scheduling goals in OKP, namely ASAP (as soon as possible) production and JIT (just in time) production.     

The relative importance of planning and control systems in achieving good delivery performance

Amongst factors such as quick changeovers and workforce flexibility, managers in 533 UK manufacturing plants ranked a responsive planning and control system as the most important facilitator of good delivery performance on products made-to-order or assembled-to-order. The rankings indicate greater importance to companies in the Household and Engineering sectors than in Process and Electronics, where other factors are dominant. These results are combined with data such as customer lead times and item variety, to characterize and explain differences between the plants in these four sectors. Collectively the results indicate considerable differences in the production planning and control tasks. This implies that general statements on the importance of planning and control systems are inadequate. Practitioners need contextual information in order to ascertain when research is applicable to their circumstances.     

An evaluation of product commonality and group technology production methods in a pre-defined multiple-machine scenario

Group technology has been used successfully for a number of years as a setup reduction tool. It is especially valuable in low-volume high-mix manufacturing environments where products and machines may be partitioned into product families and machine cells. The partitioning of machines or processes into cells may be limited by practical constraints, and the partitioning of products is complicated as the number of products and processes increases. In this paper, the authors examine the behaviour of various grouping strategies lauded as being appropriate in situations where machine partitioning and product routeing are determined by technological constraints. Of specific experimental concern in this paper is the effect of the mean and variance of component part commonality between products on system performance under various grouping strategies in a multiple-machine environment.     

A Comparative Analysis of Master Production Scheduling Techniques for Assemble-To-Order Products

This paper studies the master production scheduling (MPS) activity of manufacturing firms that produce assemble-to-order (ATO) products. It describes four techniques for master scheduling ATO products: end-product bills, modular bills, super bills, and percentage bills. These procedures are compared in terms of the percentage of customer orders delivered late, the mean tardiness of customer order deliveries, and the total cost of inventory using simulation analysis. The results indicate that the performance of an MPS technique is affected by the level of uncertainty of the end products' demands and the degree of component commonality in the product structure. In particular, modular bills produce the highest customer service level and super bills produce the lowest total inventory cost under most operating conditions. The conclusions also suggest that the choice of a particular MPS technique is often a compromise between the benefits of improved MPS performance and the costs of implementing and executing the MPS system.     

Lead time adjustment through scrap management

In a discrete parts manufacturing environment, it is necessary to compensate for the decreasing planned batch size resulting from production of scrap (defectives) in the production line, by increasing the planned production volume. This calls for a revision in the initially computed manufacturing lead time (MLT). A survey of the literature reveals that although issues related to product quantity regeneration have been studied in detail, little has been done to assess the impact on manufacturing lead times. This paper discusses the impact of scrap on manufacturing lead time in a shop with an intermittent-flow, bath-oriented, discrete-parts manufacturing environment, producing make-to-stock items.     

An intelligent workstation controller for integrated planning and scheduling of FMS cell

This paper presents an experimental design developed to determine a combination of robust planning and scheduling rules for an intelligent workstation controller (IWC). The IWC is used as part of the control system for an automated flexible manufacturing system. A three-level hierarchical control structure (shop, workstation and equipment)is adopted in order effectively to control a shop-floor. At the top level is a shop controller which receives orders and their associated manufacturing information, and manages interactions among workstations. The IWC defines and resolves the production control activities necessary to coordinate a group of equipment controllers so as to ensure the completion of orders. Specifically, the IWC is responsible for selecting a specific process routeing for each part, allocating resources, scheduling and coordinating the activities across the equipment, monitoring the progress of activities, detecting and recovering from errors, and preparing reports. These activities are accomplished using planning, scheduling, and execution functions. In order to demonstrate the effectiveness and robustness of the IWC, all the controllable and uncontrollable factors need to be identified and detailed. Controllable factors are those which are set by the controller and cannot be directly affected by the production environment. Uncontrollable factors are those which vary with the production environment and cannot be directly changed by the controller developer. The objective of the paper is to illustrate how a good set of controllable factors that dictate the IWC's effectiveness and robustness over various uncontrollable factors can be determined. Due to the number of possible combinations of all the factors, a complete validation of the effectiveness and robustness of the IWC is extremely time consuming and far beyond the scope of this paper. Therefore, a few planning and scheduling strategies are selected and a formal experiment is conducted. The experiment illustrates how significant performance dependencies for various planning and scheduling strategies can be identified.     

Open Order Rescheduling in Job Shops with Demand Uncertainty: A Simulation Study

This paper addresses the problem of open order rescheduling in a job shop. Results are reported of experiments conducted in a simulation model of an 8-machine job shop. Four different order updating policies are examined. The due-date process is modeled to include several realistic features about the pattern of due-date variability. These features are parameterized and tested at several levels. Tardiness results indicate that open order rescheduling is beneficial only when allowances are loosely set. The results indicate that inventory performance is improved by order rescheduling, particularly in cases when due dates are revised to earlier times than originally forecast.     

Scheduling algorithms for computer-aided line balancing in printed circuit board assembly

Generalized flexible flow line (GFFL) is a scheduling environment comprising several machine banks which the products visit in the same order but can skip some machine banks. The type of machines in a bank can differ but they are suitable for performing the same manufacturing tasks. To change one product to another demands a set-up operation of the machine. This paper describes several scheduling algorithms for the GFFL problem. The overall structure of these algorithms is similar, consisting of machine allocation and sequencing phases. The algorithms have been integrated into an interactive production scheduling system for electronics assembly. Sample cases are used to illustrate the operation of the system in practice.     

A METHODOLOGY FOR LABOR SCHEDULING IN A SERVICE OPERATING SYSTEM

In the increasingly competitive services sector, utilization of the labor force can make the difference between profits or losses. Until recently, service operations managers had a limited set of tools, most of them computer-based, for scheduling labor. This paper offers a manual heuristic for labor scheduling that outperforms traditional algorithmic solution approaches. Specifically, this study examines the problem of scheduling employees in service delivery system subject to demand variability. The manual heuristic proposed asigns full-time empolyees to weekly work schedules with the objective of minimizing the total number of labor hours scheduled. The performance of the manual heuristic is compared to the classical algorithmic solution and to a lower bound for a variety of demand distributions and system operating conditions. The heuristic is shown to produce a smaller work force than the classical approach in 106 of the 108 demand-operating condition patterns examined.     

MEASURING MASTER PRODUCTION SCHEDULE STABILITY UNDER ROLLING PLANNING HORIZONS

Maintaining a stable master production schedule (MPS) is difficult for many firms, especially when material requirements planning is used to manage production operations. This paper is concerned with the problem of measuring MPS stability, and the impact on stability of three important decision variables in managing the MPS within a rolling-horizon framework in a make-to-stock environment: the method used to freeze the MPS, the proportion of the MPS frozen, and the length of the planning horizon for the MPS. Simulation experiments conducted to determine the impact of these decision variables, as well as other important product demand and cost characteristics, on MPS stability are reported. The results indicate MPS stability can be influenced by managerial action directed toward management of the MPS as well as changes in important product cost and requirements characteristics.     

Alternate Routing Strategies in Batch Manufacturing: An Evaluation

Batch manufacturing firms are experiencing significant changes because of technological developments in work center design, such as flexible manufacturing systems (FMS) and planning/control tools like computer-aided process planning (CAPP). These new developments provide production managers with some solutions to a number of complex problems. For example, numerical-controlled (NC) machine center installations are effective in providing quality parts because of tight tolerance specifications built into the equipment. However, these highly efficient centers create bottlenecks that constrain shop throughput, since production planners tend to rely too much on them. To help improve manufacturing planning, we introduce an important element to the batch production scheduling component of CAPP's mission—evaluating possible alternate routes. Production scheduling encompasses job route selection as well as machine center assignment (loading), job releasing, and setting due dates. In this paper, three routing strategies requiring different levels of shop floor information are tested and evaluated using computer simulation. Shop performance is measured by total cost and traditional measures of job flow time, lateness, and tardiness.     

Concepts,Theory, and Techniques A JOINT LOT-SIZING RULE FOR FIXED LABOR-COST SITUATIONS

Many American firms are implementing just-in-time production in order to minimize inventories, reduce flow time, and maximize resource utilization. These firms recognize that, in the short run, setup costs really are fixed expenses and it is available capacity which is the critical factor in determining production-run quantities. We propose using available capacity to increase the number of setups and reduce lot-size inventories. This results in improved relevant cost performance. Sugimori, Kusunoki, Cho, and Uchikawa [16] in their paper on the Toyota kanban system developed a relationship for lead time but failed to use it for lot sizing. We use this relationship to develop the joint lot-sizing rule. The efficacy of our proposed rule is demonstrated by applying it to lot-size scheduling problems at the John Deere Engine Works [14]. Extensions of the proposed rule to undercapacity situations with material-wastage costs in the setup processes and to multistate production inventory systems also are discussed.     

Production planning and control tools

There are numerous tools available to be used for production planning and control purposes. The number of tools is ever increasing, and so are the levels of sophistication as well as complexity. For the specific manufacturing firm, the task of selecting the most appropriate set of tools is not trivial. However, in recent years, the understanding of the relationship between tools and manufacturing environments for which they are suitable has increased. The purpose of this paper is to provide an overview of production planning and control tools available today, as well as new trends, issues and ideas.     

Simplest strategies method for manufacturing workcell restoration

We consider the production process of a manufacturing workcell. Production items obtained from an outside supplier are not processed adequately as far as their quality is concerned. Production items meeting the required quality depend on the workcell state, which degrades according to the number of produced items. The workcell is completely restored by some restoring operations leading to its as-new condition. The method of deriving the restoration period, which leads to the maximum probability that produced items meet the required quality, is introduced. It is based on the nontraditional approach, i.e. on the simplest strategies method for the formulation of the problem presented here. The implementation of this optimization approach is illustrated with an example.