Manufacturing planning and control approaches: market alignment and performance

The design of manufacturing planning and control (MPC) systems is a strategic decision for manufacturing operations. In this paper we analyze the interrelationships between the choice of MPC approaches at different hierarchical levels with market requirements and operational performance. These relationships are explored through an extensive survey comprising responses from 128 manufacturing firms. The results show that the choice of MPC approaches, primarily at the sales and operations planning and master scheduling levels, has a significant mediating role in improving performance. The alignment between market requirements and the choice of MPC approaches is significant and has a significant impact on performance. In a dynamic environment, the choice of MPC approaches is shown to have a positive mediating effect on operational performance.     

Product flexibility in selecting manufacturing planning and control strategy

The manufacturing systems capable of producing several products simultaneously are frequently subject to changes in product types due to demand fluctuations. In such systems a product flexible manufacturing planning and control (MPC) strategy is needed to change from one product type to another with minimum deterioration to system performance levels. The objective of this research is to develop a systematic analysis and evaluation approach in order to compare the MRP-push and JIT-pull strategies quantitatively based on a product flexibility measure. A new product flexibility measure is developed based on the sensitivity to change concept and presented together with the implementation in a real manufacturing system. Simulation is used to compare the performance of a JIT-pull with an MRP-push strategy based on performance measures, e.g. manufacturing lead time, work-in-process inventory, backorders, machine utilization and throughput. The performances of the two strategies are evaluated in two scenarios: (i) a single product; (ii) a second product is added (the first product being simple and the second being complex in terms of processing). The impacts of adding the second product on the performance measures for the push and pull strategies are then assessed. A multi-attribute evaluation scheme is used to compare the two strategies where the attribute values are the change in performance measures as the second product is added. The proposed product flexibility measure is utilized in the interpretation of the results.     

A distributed multi-agent environment for product design and manufacturing planning

This paper describes a multi-agent approach to the integration of product design, manufacturability analysis, and process planning in a distributed manner. The objective is to develop a distributed concurrent engineering system to allow geographically dispersed entities to work cooperatively towards overall system goals. In the paper, an agent-based concurrent engineering system concerning product design and manufacturing planning, and its fundamental framework and functions are presented. The proposed model considers constraints and requirements from the different product development cycles in the early development phases and fully supports the concept of design-for-manufacturability. This methodology uses conflict resolution (CR) techniques and design-improvement suggestions to refine the initial product design. The model comprises a facilitator agent, a console agent and six service agents. Each service agent is used to model different product development phases, and the console agent acts as an interacting interface between designers and the system, while the facilitator is responsible for the decomposition and dispatch of tasks, and resolving conflicts of poor designs. A prototype system for part design, manufacturability analysis, and process planning has been implemented. The performance of the prototype system shows that it could be extended to include other service agents, such as assemblability analysis, to become a comprehensive distributed concurrent engineering system for geographically dispersed customers and suppliers.     

Theory and practice of manufacturing strategy

This paper first proposes a methodology for manufacturing strategy development based on a critical review of the theory of manufacturing strategy. The methodology captures the essential factors that must be considered, and the steps that must be taken, by a firm attempting to design a viable manufacturing strategy. An exploratory study of the process of formulating and implementing manufacturing strategy practised by three firms is conducted. Their experiences in the manufacturing strategy process are reported and analysed. While the practice of each firm is different, the process of manufacturing strategy formulation seems to be in line with the conceptual models discussed in the literature. Our findings offer some evidence that manufacturing is slowly shedding its image as the ‘missing link’ in corporate strategy. While managers of the studied firms are fully aware of the competitive advantages that manufacturing can provide, they are not totally committed to articulating a manufacturing strategy because of concerns about its successful implementation. It is proposed that further research on manufacturing strategy focus on such implementation issues as the infrastructure, corporate culture, performance measurements, decision-making and managerial styles.     

Design in small manufacturing companies in Scotland

This paper gives the results of a survey of small manufacturing companies in Scotland with reference to their managers' understanding of and attitudes towards design; their control of the product design/development process; the communication of design objectives within the firm and forward planning for new product development. The survey revealed a generally positive attitude to design in the companies visited and the crucial role of both suppliers and customers in ensuring the success of the design activity.     

Partial least square-based model predictive control for large-scale manufacturing processes

The Model Predictive Control (MPC) method has been widely adopted as a useful tool to keep quality on target in manufacturing processes. However, the conventional MPC methods are inadequate for large-scale manufacturing processes particularly in the presence of disturbances. The goal of this paper is to propose a Partial Least Square (PLS)-based MPC methodology to accommodate the characteristics of a large-scale manufacturing process. The detailed objectives are: (i) to identify a reliable prediction model that handles the large-scale "short and fat" data; (ii) to design an effective control model that both maximizes the required quality and minimizes the labor costs associated with changing the process parameters; and (iii) to develop an efficient optimization algorithm that reduces the computational burden of the large-scale optimization. The case study and experimental results demonstrate that the presented MPC methodology provides the set of optimal process parameters for quality improvement. In particular, the quality deviations are reduced by 99.4%, the labor costs by 84.2%, and the computational time by 98.8%. As a result, the proposed MPC method will save on both costs and time in achieving the desired quality for a large-scale manufacturing process.     

Optimal process parameter determination for computer‐aided manufacturing

Producing high‐quality products at low cost is one of the key factors to survival for manufacturing sectors in today's intense global competition environment. One way to gain competitiveness is to integrate product design and process planning into one activity. This study attempts to determine optimal process parameters for a manufacturing process under given design parameters. The process parameters to be determined in this study include process means and process tolerances for particular manufacturing process sequences. The problem is formulated in constrained non‐linear optimization, considering both quality‐ and manufacturing‐related costs. The proposed application evaluates alternative product designs and process sequences so that the best associated process parameters can be determined during the early stages of design and planning. This makes the link between CAD and CAM systems more useful and effective. As a result, optimal integration of product design and process planning with minimal production costs and maximal product quality is possible. Copyright © 1999 John Wiley & Sons, Ltd.     

Applying the TOC thinking process in manufacturing: A case study

A case study is presented to illustrate the application of the Theory of Constraints thinking process logic tools in a manufacturing environment. The study firm performs design activities related to meeting future product requirements while concurrently meeting existing production schedules for the current design of the product. Current approaches to managing the firm's limited productive capacity do not allow for both design and production activities to occur simultaneously while meeting the customer's current product delivery schedule. Thus, despite their desire to satisfy their customer's future design requirements, management uses the majority of its production capacity to meet its customer's current product delivery schedule. This case study demonstrates how a team of employees used thinking process logic diagrams to document reality, identify a core conflict and problem, develop proposed changes to address the core problem, and create several detailed action plans to implement changes within the study organization. Initially, scenarios associated with some undesirable effects are used to understand how prevailing policies and behaviours result in less than desired production line performance. Then, a current reality tree is constructed to link the core problem or system constraint with the previously identified undesirable effects. Next, two major injections are developed to address the core problem in managing the production line as logically documented in a future reality tree. Finally, three transition trees are presented to guide the implementation of change at the study organization.     

新型陶瓷快速成型装置数控系统的研究

基于GT400运动控制器的开放式体系结构的数控系统软硬件平台及其关键技术,研究陶瓷零件快速成型设备数控系统对于缩短陶瓷零件的制造周期以及提高企业的生产效率所具有的重要意义.阐述了陶瓷零件快速成型机的新工艺方法和特点,对新型陶瓷零件快速成型机机械系统及其控制要求作了详细分析,着重介绍了陶瓷零件快速成型机控制系统的硬件设计及自顶向下的软件设计.利用Visual C++6.0开发工具和GT系列运动控制器自带的DLL动态链接库开发了操作方便、运行稳定、加工精度高的开放式陶瓷快速成型装置数控系统.控制系统能够很好地满足系统开放性的要求及产品自动化生产的要求,提高了经济效益.     

A heuristic for formulating within-plant manufacturing focus

The concept of manufacturing focus suggests that each plant is assigned a unique set of manufacturing tasks derived from the firm's competitive strategy. Many empirical studies have verified the importance and benefits of manufacturing focus in enhancing a firm's competence in the market. Nonetheless there is no methodology offered for designing such a manufacturing system with considerations of resource requirements although the need has been recognized. In this study, we propose a methodology that can help managers arrive at a manufacturing focus design within a plant. Because of the large size and nonlinear nature of the problem, a heuristic solution is proposed. The heuristic translates the strategic concept of competitive priorities into management parameters, thereby allowing incorporation of market factors into manufacturing process design. Experimental results show that the proposed methodology offers managers the opportunity to generate and assess alternative focus designs which are otherwise unavailable. The use of the heuristic is straightforward in practical situations and should greatly facilitate the achievement of manufacturing focus with minimal resource requirements. Overall, this research provides an analytical framework for further research in focused manufacturing.     

Towards intelligent manufacturing planning and control systems

In this paper, we review some well-known manufacturing planning and control (MPC) systems and models, and highlight both their advantages and major drawbacks. The analysis indicates that various important planning and control problems, as they arise in industry, are not properly addressed by current MPC systems. A well-known production system typology, illustrated by industrial examples, is briefly discussed to further highlight these planning and control problems. Next, we define a basic framework architecture for planning and control in both make-to-stock and make-to-order systems. The emphasis in this framework is on an integration of technological and logistics planning, and on an integration of capacity planning and materials coordination issues. In addition to this architecture, we further define an algorithmic framework that explicitly aims at the latter integration. To complete the architecture, we suggest a variety of procedures and algorithms to implement in the various modules.     

Integrative process plan model and representation for intelligent distributed manufacturing planning

Process planning is one of the key functions for product design and manufacturing. Process plans have very great impact on all phases of product design and manufacture. Therefore, it is necessary to establish a high level of interaction between different product design activities and their tight integration into a coherent system. In this paper we describe a process plan model that allows for such integration. The framework for integration is briefly described and the process plan model that considers three dimensions of planning is explained. The manufacturing process plan model is defined as a three-dimensional model with the following dimensions: time/order, variability/alternatives, and aggregation. All three dimensions are defined and explained as they relate to overall manufacturing planning. The nature of these dimensions is illustrated with several examples. The implementation of the framework and the model within the distributed system IMPlanner is presented. The prototype has been implemented in the Java language and the model for data storage has been implemented in XML. The benefits of integrated consideration are described for several currently implemented applications such as feature modelling, process visualization, process network generation, cell formation, and scheduling.     

A method for the concurrent design and analysis of networked manufacturing systems

Multistage manufacturing processes (MMPs) require multiple stations and operations. Traditionally, analysis of MMPs focused on material planning and control strategies. For a given MMP, the effect of the strategy on the volume and rate of production, ability to handle product type variability, and the effects of process variability on production rate, on-process inventory, etc., have been studied individually. Such approaches, while necessary, do not address the combined effects of MMP design choices on the final product quality. In this article, a method based on the compromise decision support problem and stream of variation model is proposed to provide a way to evaluate suitable designs for the implementation of MMPs. Using the dimensional quality of the product as a measure of quality, the proposed method is illustrated using a three-stage MMP in an automobile panel stamping process while considering the conflicting requirements of diagnosability and controllability.     

Agile manufacturing system control based on cell re-configuration

The control of an agile manufacturing system (AMS) is expected to be flexible, open, scalable and re-configurable so as to tackle the more complex and uncertain information flows. To meet these requirements, we propose agent-based control architecture for AMS, under which the functions of task planning, scheduling and dynamic control are integrated seamlessly. First of all, this paper introduces the concept of RMC (re-configurable manufacturing cell), based on which, we construct the control architecture for AMS in compliance with multi-agent system (MAS). The whole control process under the architecture comprises two hierarchies, i.e. the upper one for order planning and RMC forming and the lower one for task scheduling within each RMC. For the upper hierarchy, we establish a linear integer programming (LIP)-based mathematical model and a MAS-based dynamic process model, and present a two-step approach to order planning and RMC forming. For the lower hierarchy, we develop the scheduling model, a method based on the bidding mechanism from contract net, and describe the rescheduling mechanism in the control system. To illustrate the methodology proposed in the paper, a simulation study is thoroughly discussed. Our studies demonstrate that the RMC-based control architecture provides an AMS with an optimal, dynamic and flexible mechanism of responding to an unpredictable manufacturing environment, which is crucial to achieve agility for the whole manufacturing system.     

Distributed product and facility prototyping in extended manufacturing enterprises

In order to reduce the cost at the early product development stages, the planners need methodologies and tools that would allow them to judge upon the implications of the product design on the required manufacturing processes and facilities for their production. This paper reports on a new theoretical platform and a pilot implementation of a decision-making environment for distributed product and facility prototyping in an extended enterprise. The approach is based on an exchange of requests and information between collaborative autonomous agents that support the design, manufacturing planning and facility formation activities. The decision-making is formalized as iterative matching of design, process and facility attributes using multilevel resource capability representation within the extended enterprise. The system is implemented as an XML/CORBA-based environment for conveying design and manufacture messages across traditional technology boundaries. The reported research aims to provide the designers with a rapid manufacturing feasibility assessment tool to be used at different design and planning stages in extended manufacturing enterprises.     

Case studies based development of a rule-base for the specification of manufacturing planning and control systems

Research and development in Information Technology is increasingly turning to techniques popular in social science fields for the design, testing and validation of new systems. Case studies, in particular, are used as a powerful technique in all areas of system development and research. Manufacturing Planning and Control (MPC) systems are typical of such systems where the problems are no longer predominantly technical. One of the main barriers to the implementation of successful MPC systems is accurate identification of the true user requirements. This paper describes the use of multiple case studies for the development of a rulebased system for the specification of suitable MPC systems in manufacturing companies. The case studies are carried out in an iterative manner to enable the rule-base to be updated and re-tested with each successive cycle. The use of multiple case-study research cycles enables the accuracy and usability of the rulebase to be assessed as the research progresses. The rule-base comprises inputs (company characteristics and management concerns), rules (structured around reasoning) and outputs (recommended MPC system activities). It is shown that it can be expected to be greater than 90% accurate for any small to medium sized enterprise (SME) engaged in batch manufacturing.     

Agile manufacturing: Enablers and an implementation framework

Tougher competitive situations have led to increasing attention being paid to customer satisfaction, of which timely and customized services are the key concepts. As the product life cycle becomes shortened, high product quality becomes necessary for survival. Markets become highly diversified and global, and continuous and unexpected change become the key factors for success. The need for a method of rapidly and cost-effectively developing products, production facilities and supporting software, including design, process planning and shop floor control system has led to the concept of agile manufacturing. Agile manufacturing can be defined as the capability to survive and prosper in a competitive environment of continuous and unpredictable change by reacting quickly and effectively to changing markets, driven by customer-designed products and services. This article details the key concepts and enablers of agile manufacturing. The key enablers of agile manufacturing include: (i) virtual enterprise formation tools/metrics; (ii) physically distributed manufacturing architecture and teams; (iii) rapid partnership formation tools/metrics; (iv) concurrent engineering; (v) integrated product/production/business information system; (vi) rapid prototyping tools; and (vii) electronic commerce. A conceptual framework for the development of an agile manufacturing system and future research directions are presented in this paper. This framework takes into account the customization and system integration with the help of business process redesign, legal issues, concurrent engineering, computer-integrated manufacturing, cost management, total quality management and information technology.     

Aligning marketing and manufacturing strategies with the market

In strategic marketing decisions substantial emphasis is placed on market segmentation and product/service differentiation. This follows from separate, intensive analyses of customers and competitors. Based on these analyses, the resultant segmentation and differentiation schema, and an intensive review of the firm's own strengths, weaknesses, opportunities and threats, the firm makes one of its most important and critical decisions: which customers to serve and which products to emphasize, referred to as positioning. On the other side of the same corporate coin, manufacturing makes decisions on process and infrastructure investments based upon the technologies required, and its perception of what it needs to do well in order to fulfil its role. In the same way as with marketing decisions, the firm now makes another of its most critical decisions by committing itself to major investments in manufacturing that are characterized by high value and long time scales to change. On the one hand, these positioning decisions by marketing invariably include little emphasis in determining the customer requirements that must be supported by manufacturing, and fail to investigate the ability of manufacturing to support these requirements. On the other hand, manufacturing decisions do not reflect key insights on the needs of current and future markets. As a consequence, many businesses fail to achieve their strategic business objectives, due, in part, to the inability of marketing and manufacturing to jointly develop consistent strategies. We call this a lack of alignment. The methodology outlined in this paper concerns how to align marketing and manufacturing strategies by using markets as the center piece of both developments. Doing this highlights the recognition that markets need to form the common denominator of both marketing and manufacturing strategy development. This methodology is illustrated by using an actual example drawn from plant-based research. Several key questions are addressed in this methodology. How does marketing view customers and markets? What is manufacturing's view of the same customers and markets? To what extent is manufacturing actually able to support the demands that these customers and markets are placing on a firm's capabilities? It is important to check with the use of data, the actual operating performance against the required capabilities. In cases where substantial differences exist between customer and market requirements and manufacturing capabilities, strategic options (both in marketing and manufacturing) to resolve these differences need to be addressed in making strategic business decisions.     

Combined parameter and tolerance design optimization with quality and cost

The need to remain competitive for survival in the current world market has led manufacturing sectors to consider the low cost and high quality of product and process design. Production of quality products at low cost in today's manufacturing industry requires simultaneous consideration of product design and process planning, particularly in the early stage of design and planning. During product design, parameter design determines the design target (design setting) and tolerance design determines design tolerance. During process design, the parameter design determines the process mean (process setting) and tolerance design determines process tolerance. This study provides a mathematical relationship to link the elements of design target, design tolerance, process mean and process tolerance in one equation. By following this equation, manufacturability for all possible combinations of product and process design can be ensured, which increases the flexibility of both product design and process planning. With this in mind, an analysis model that includes manufacturing cost and quality loss simultaneously has been developed to determine the optimal values of design tolerance, process mean and process tolerance. The proposed model provides a method of combining the optimization of parameter and tolerance design over product/process in the early stage of design.     

Dynamic control in automated manufacturing: a knowledge integrated approach†

Flexibly automated facilities permit a wider variety of products as well as objectives for making those products—thus requiring manufacturing control strategies to face an environment of ever present change. To operate in this environment, a system composed of hard automation, flexible automation and humans, which can be responsive to product and process requirements, machine breakdowns and delays, engineering changes and improvement opportunities, is needed. Such a system does not fall into the realm of any current manufacturing solution techniques. Something more than exact optimization, heuristic algorithms or stochastic estimates must be utilized. The research discussed herein describes a dynamic solution strategy to operate in this changing environment with adaptive self-improving characteristics. The proposed methodology for optimizing the control of an automated manufacturing facility is an integrated approach utilizing real-time feedback from the operating facility, direct feedback from a simulation of the facility and guidance from a historical knowledge base. This system is being implemented in a knowledge based environment called CAYENE. CAYENE is a hybrid artificial intelligence system, written in Lisp, based on the idea of using object oriented programming as a unifying principle for functional, frame and rule-based programming.