Implications of selected production planning functions: Impact analysis through simulation

When capacity differences are minimized through an efficient algorithm, and integration of capacity planning with any production planning system is performed, it affects some elements of production planning functions. In the reverse way, some elements of production planning and management techniques also affect the effectiveness of capacity planning. These happen because capacity planning processes, production planning processes and production management techniques are not standalone sub-systems, rather these are totally dependent on each other. This paper aims at determining and formulating the effects of some of the selected elements of capacity and production planning functions on each other. This study is conducted using simulation in object-oriented SIMPLE+ + system.     

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.     

Multi-site aggregate production planning with multiple objectives: A goal programming approach

This paper addresses the problem of aggregate production planning (APP) for a multinational lingerie company in Hong Kong. The multi-site production planning problem considers the production loading plans among manufacturing factories subject to certain restrictions, such as production import/export quotas imposed by regulatory requirements of different nations, the use of manufacturing factories/locations with regard to customers' preferences, as well as production capacity, workforce level, storage space and resource conditions of the factories. In this paper, a multi-objective model is developed to solve the production planning problems, in which the profit is maximized but production penalties resulting from going over/under quotas and the change in workforce level are minimized. To enhance the practical implications of the proposed model, different managerial production loading plans are evaluated according to changes in future policy and situation. Numerical results demonstrate the robustness and effectiveness of the developed model.     

Experimental earliness/tardiness production planning with the due window system

In order to use the philosophy of JIT to improve the production planning method of MRP-II, we propose the experimental software system of the earliness/tardiness produc tion planning problem with due window. By means of the approaches and model reported in this paper, the optimal production planning can be achieved. The recommended model extends the problem of due window from the shop scheduling level into the aggregated planning level of mass manufacturing systems. Simulation results have demonstrated that the experimental software is a useful tool for the production management of repetitive manufacturing enterprises.     

Computational complexity of algorithms for MRP and JIT production planning problems in enterprise resource planning systems

An enterprise resource planning system (ERP) is the information backbone of many manufacturing companies. At the core of ERP is a conventional material requirements planning (MRP) production planning system or a variation of MRP when just-in-time (JIT) principles are used in manufacturing. MRP and JIT both organize production planning into a hierarchy of long-, medium- and short-range problems. In all there are eight different problems. Some are common to MRP and JIT, others are specialized for a particular system. This paper analyses the computational requirements of these problems. This is important for ERP because it plans for large numbers of products (e.g. 50 000 products at 3M Company and 44 000 products at States Industries in Oregon) at large numbers of locations (e.g. 82 locations in 21 countries for Visteon Automotive Systems of Michigan and 19 locations at Boeing). We show that adequate algorithms exist for some problems, but better algorithms are needed for other problems if ERP is to provide useful production plans.     

Period batch control: Classic,not outdated

Period Batch Control was developed and first applied during the Second World War. The historic roots are discussed and the principles of this classic production planning approach explained, PBC compared to other production control concepts, and it is demonstrated that it may still be fruitfully applied, especially in combination with cellular manufacturing. It is therefore considered as a classic, but not outdated production planning concept.     

Cloud manufacturing system for sheet metal processing

Abstract

Cloud computing is changing the way industries and enterprises run their businesses. Cloud manufacturing is emerging as an approach to transform the traditional manufacturing business model, while helping the manufacturer to align production efficiency with its business strategy, and creating intelligent factory networks that enable collaboration across the whole enterprise. Many production planning and control (PPC) problems are essentially optimisation problems, where the objective is to develop a plan that meets the demand at minimum cost or maximum profit. Because the underlying optimisation problem will vary in the different business and operation phases, it is important to think about optimisation in a dynamic mechanism and in a number of interlinked sub-problems at the same time. Cloud manufacturing has the potential to offer decision support as a service and medium of communication in PPC. To solve these problems and produce collaboration across the supply chain, this paper provides an overview of the state of the art in cloud manufacturing and presents a model of cloud-based production planning and production system for sheet metal processing.     

Flexible reasoning using sensible agent-based systems: A case study in job flow scheduling

Planning and control systems for highly dynamic and uncertain manufacturing environments require adaptive flexibility and decision-making capabilities. Modern distributed manufacturing systems assess the utility of planning and executing solutions for both system goals (e.g. minimize manufacturing production time for all parts or minimize WIP) and local goals (e.g. expedite part A production schedule or maximize machine X utilization). Sensible Agents have the ability to alter their autonomy levels to choose among a set of decision models in order to handle the differences between local and system goals. In this paper, Sensible Agents are applied to a production planning and control problem in the context of job shop scheduling and decision model theory. Sensible Agents provide for trade-off reasoning mechanisms among system and local utilities that are flexible and responsive to an agent's abilities, situational context and position in the organizational structure of the system.     

MRP system performance under lumpy demand environments

Material requirements planning (MRP) systems are deemed to deal with master schedules with lumpy demand patterns better than any other production scheduling system. Past studies have advocated important advantages of using MRP systems. The objective of this paper is to look into the impact of patterns of demand lumpiness on the performance of MRP systems by a simulation study. Results show that there is an important threshold point in terms of degree of lumpiness at which MRP system performance starts to deteriorate in the operating conditions considered. If master production schedules (MPS) can be controlled by manufacturers, MRP users should exercise caution to introduce demand lumpiness in MPS to improve system performance. If not, MRP users should then examine the given lumpiness and choose an appropriate lot-sizing rule that has been shown to take advantage of the effect of demand lumpiness.     

Selection and implementation of a PPC system

There are many computer-aided production planning and control (PPC) systems available on the market which can provide a solution to the complex task of production planning and control. However, the question remains, how can a company find an optimal system from the vast amount of available systems? This article proposes that a company, having decided to buy one of the available systems, starts a project for selection and implementation of the PPC system.     

Simple systems for computer-aided production management

Future production concepts where workshop employees responsibly carry through planning and scheduling tasks call for new principles ofcomputer-aided production management (CAPM). With the aid of a critical analysis ofdifferent planning and scheduling mechanisms it will first be laid down why the field of computer-aided production management is suited for a dialogue-oriented planning support based on simple models rather than for the objective of automation with the aid of refined optimization algorithms. Consequently, an alternative design is proposed. This is a prototypically realized concept aiming at computer-aided support of production management of production teams.     

A framework for production control in health care organizations

The paper presents a hierarchical framework for production control of hospitals which deals with the balance between service and efficiency, at all levels of planning and control. The framework is based on an analysis of the design requirements for hospital production control systems. These design requirements are translated into the control functions at different levels of planning required for hospital production control. The framework consists of five levels of planning and control: patient planning and control, patient group planning and control, resources planning and control, patient volumes planning and control and strategic planning, though this last level does not make part of production control as such. Each of the levels of the framework is further elaborated in terms of the decisions made regarding patient flows and resources, and the co-ordination of the different planning levels. Implications of the framework are discussed by describing some points where current practice deviates from assumptions made in our approach. Recommendations for future research and development of the planning framework are formulated.     

Production planning and inventory control in a company manufacturing PC parts: A case study

In this paper, we present a case study on the production planning and inventory system in a company manufacturing personal computer (PC) parts. In the case study, the targets are specified for developing a system for production planning and inventory control. The current state of the company is analysed for clarifying the points necessary to achieve the targets. Also, a system based on the analysis is proposed and its effects are estimated.     

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.     

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.     

Integration of CAD/CAM and production control in sheet metal manufacturing — an application area of operations research

Abstract

This paper describes a process planning system for sheet metal parts. This system has capabilities to deliver process planning data just in time. The change of tools, processes and even machines for manufacturing of the parts is possible at the shop door after design has been finished.

The sequence of the production planning steps carried out can be changed. In this way the system can be adapted to the requirements of different sheet metal manufacturing companies.

More detailed information is given about the methods used for nesting of the workpieces on the sheets to be produced.     

Allocation of buffer capacity to minimize average work-in-process

This paper proposes an efficient heuristic algorithm to solve the problem of allocating the buffers in a production line for given total buffer capacity and the minimum required throughput. While the traditional research has focused on the problem of allocating the buffer capacity to maximize the throughput, the objective of minimizing the average Work-In-Process (WIP) is considered. Minimization of the WIP in the production line has drawn much attention in many practical applications, due to the growing efforts in reducing the production lead times for faster customer response. Two heuristics are proposed and compared to solve the problem. One is a very simple heuristic approach, and the other is a modified 'Non-SEVA' (Non-Standard Exchange Vector Algorithm) which was originally proposed by Seong et al . ( International Journal of Production Research, 33, 1989-2005, 1995) for the throughput maximization problem. Through computational tests, the efficiency of the proposed approach is shown.     

Improving throughput for an electronic assembly line using a constraint analysis methodology

Electronic assembly operations are vital to industries such as telecommunications, computers and consumer electronics. This paper presents a constraint analysis methodology for planning and improving electronic assembly operations that draws on concepts from queueing theory, simulation and production planning. The proposed methodology identifies the operational bottleneck and predicts the utilization, throughput and lead time of the assembly line. It also quantifies the relationship between yields and utilization for the assembly operations. A case study is presented that applies the methodology at an Ericsson, Inc., telecommunications equipment assembly facility. The constraint analysis methodology provided valuable decision support as the managers of Ericsson evaluated the costs and benefits of additional production capacity. Although the focus of this paper is electronic assembly operations, the methodology can be applied to general flow line assembly systems with feedback loops for test and rework under dedicated high-volume production.