Dynamic issues in the planning and control of integrated manufacturing hierarchies

Integrated manufacturing operations typically are organized along hierarchical lines. Characterized by product aggregation and time horizon, hierarchical decompositions aim at easing problems associated with the complexity and scale of the manufacturing function taken as a whole. Static models have been developed and employed which facilitate the analysis and functioning of these organizations. Existing models are valuable aids in assisting goal-planning functions, but provide little guidance for directing the pursuit of goals. This paper presents a new hierarchical model of integrated manufacturing operations based on concepts of management control. The model is congruent with commonly used static planning models, while at the same lime depicting real-time, goal-achievement efforts within a dynamic operating environment. Emphasizing the interactions between goal planning and goal achievement, the dynamic model provides a means of assessing the effects of decentralization and autonomy on the goal planning and achievement process. The model is used to identify two resource-consuming chain reactions linked to replanning and goal pursuit within the hierarchy. A simple example based on the dynamic extension of a typical static decomposition illustrates the key findings.     

Push-Kanban – a kanban-based production control concept for job shops

Job-shop production in an individual and small-batch manufacturing environment demands producing simultaneously different products in many customised versions and in small numbers. The associated variability of the time-phased work content leads to a high degree of complexity and turbulence in the manufacturing process of such a production type. Therefore, production control becomes significantly more complicated, and many theories on how to cope fail in the real world. Despite the many technological and conceptual advances in the field of job-shop control over the past few decades, there is still a remarkable lack of practical control approaches for job-shop production. For this reason the Push-Kanban production control concept will be introduced in this article. It combines robust push scheduling along with a kanban-driven, decentralised inventory control mechanism to create a holistic control approach, integrating all production control tasks. Thus, it offers a feasible option for controlling job-shop production in industrial practice. This article examines the effectiveness of the concept by means of a simulation study based on real data.     

Production control for just-in-time tool-and-die manufacturing

The strategy to implement production control varies in different types of manufacturing systems. We address the issue of production control in unit-based manufacturing systems where the production batch size of the final product is one or two, the product is custom designed and is made up of numerous individual components with similar process routeings lor special machine tools, turbines, boilers, tool-and-die, injection moulding equipment, custom fabrication, etc. We have developed algorithms to generate master production schedules in this particular domain of manufacturing systems using the concept of workgroups. We show how a Kanban-based JIT shopfloor control and purchasing system can be implemented in such systems in tandem with an inventory management system by utilizing the concept of demand lists. We also propose a model for practical implementation of production control in this domain. The methodology is illustrated at a tool-and-die plant where a CIM software is used to apply the JIT-based production control. Preliminary results show a significant reduction in lead times. We try to show the relationship between research and industrial applications of productions of production control and how to bridge the gap between them.     

Performance analysis of a multi-agent scheduling and control system under manufacturing disturbances

This paper is concerned with evaluating the performance of alternative multi-agent approaches to manufacturing planning and control. In order to separate the influence of ‘control algorithm’ from that of ‘control architecture’, a simple local control algorithm is chosen as a common starting point for developing the agent-based system. Two sets of experiments are then reported to evaluate how changes in individual agent characteristics can affect the control system's flexibility and adaptability against disturbances. These experiments show that the manufacturing and control system performance is not affected by architecture if the control algorithm remains fixed, however, altering the characteristics of the control system decision-makers influences both systems’ performance.     

A routine-based framework implementing workload control to address recurring disturbances

Abstract

This research focuses on responsiveness in high variety manufacturing environments. To achieve it, the article proposes to develop Dynamic Response Capabilities (DRCs) of the manufacturing system defined as the abilities to readjust the planned operating parameters of workload, capacity, and lead time, in the wake of disturbances. To inform their development, built on the Workload Control theory, a routine-based framework is proposed. The framework supports an integrated approach for the implementation of adaptive decision-making routines for workload, capacity, and lead time readjustments at different stages in the order fulfilment process. Findings from two empirical cases show the appropriateness of the framework to develop and utilise DRCs in different settings of disturbances. Results of a simulation study, with one of the case companies, also shows the effectiveness of the framework to drive performance improvements in presence of recurring disturbances leading to demand variability.     

Flexibility configurations: Empirical analysis of volume and product mix flexibility

In this paper we address flexibility and investigate the relationship between volume and product mix flexibility. One view of flexibility is that of being a capability in itself; another view is that of flexibility as an enabler, providing the manufacturing system with properties on which other competitive capabilities are built. In this research, the latter view of flexibility is used, where flexibility acts as a second order competitive criterion. The aim is to differentiate between two dimensions of flexibility important to the manufacturing value chain, i.e., volume and product mix flexibility, and to investigate how different flexibility configurations are related to various manufacturing practices. A clustering research approach is used to identify groups of companies based on flexibility configurations. The groups are then analyzed with respect to characteristics and impact on operational performance. For the empirical investigation, we use empirical data from the high performance manufacturing (HPM) study, including three industries and seven countries—a total of 211 plants. We find that flexibility configurations based on high or low levels of volume and mix flexibility combinations show significant differences both in terms of operational performance, and in terms of emphasis put into different flexibility source factors.     

面向并行制造的多生产单元协同调度研究

为提升多生产单元制造系统整体效率，在其系统内开展面向并行制造的协同调度研究，在考虑运输、换线等时间的基础上，构建多生产单元并行协同调度模型，采用并行分段协同遗传算法求解；在此基础上，将所研究协同调度方法应用于某复杂机电产品多生产单元制造车间，并与变批量调度与等批量调度比较。研究表明，所提的并行协同调度方法可以显著提升生产单元效率，提高生产单元设备和人员利用率。     

Flexible manufacturing systems performance in U.S. automotive manufacturing plants: a case study

Flexible manufacturing systems (FMS) philosophy is a key weapon in achieving global manufacturing competitiveness. It encompasses a wide range of dimensions to improve all aspects of operational performance metrics. The aim of the study is to examine the current state of flexibility adoption in U.S. automotive manufacturing facilities and its impact on operational performance metrics. It utilizes survey questionnaire developed based on previous work in U.S. manufacturing industry. The survey was originally distributed to 420 facility managers in the U.S. domestic automotive industry. It was revealed that 70% of the respondents had implemented all 15 flexibility dimensions listed in the questionnaire. The data analysis conducted shows that implementation of certain flexibility dimensions will lead to significant improvement in specific operational performance metrics. This considerable finding can be used as a guide for manufacturing managers to achieve certain objectives in operational performance improvement in a rapidly changing environment.     

Total production control

The new requirements for enterprise flexibility, quality improvement, costs and throughput limes reduction cannot be achieved by using traditional approaches. While US and European industry developed the grand CIM, FMS, CAD/CAM and MRP II projects, Japan introduced just-in-time and lean production, not to demonstrate the possibilities of the new technology but to expose operational inefficiencies and waste in the manufacturing process. The main CIM effort was in the flexibility and productivity improvement, bin its implementation stressed above all the technical aspects of the factory integration and the most flexible production factor, people, remained in the background. The new technology must be implemented into the organizational framework that uses and develops the skills, knowledge and creativity of the human resources. People in the production process need a new kind of decision support in the rapidly changing business environment. A new concept, total production control (TPC), that is a reaction to the present manufacturing problems will be presented. TPC integrates many methods and tools for production system analysis and improvement, production system design and production planning and control. This concept emphasizes a preventive aspect of the problem solution in the production process and supports a production manager at the three time views: past (archive and statistical database); present (shopfloor data capture and production progress monitoring); and future (simulation and modelling tools).     

Agent-based interbay system control for a single-loop semiconductor manufacturing fab

This study investigates agent-based interbay control of a wafer fabrication facility with a single-loop track. Doing so will simultaneously resolve the production scheduling and vehicle dispatching problems for an interbay over-hoist-transportation system which is commonly employed in the semiconductor manufacturing industry. Two issues are focused on in this study: (i) To design appropriate agent-based control architecture for an interbay system and (ii) to develop a coordination mechanism for the autonomous agents in the interbay system, so that wafer manufacturing tasks can be accomplished efficiently. In this study, we construct a distributed interbay system architecture, in which wafer cassettes, vehicles, and manufacturing cells with stockers are modelled as independent and autonomous agents. This study develops an agent coordination mechanism that is based on a vehicle-initiated contract net protocol. Three types of bidding strategies are proposed and empirically examined via simulation. The performances of the proposed agent-based control mechanism, in terms of cassette sojourn time and throughput, are observed and our experiments have shown promising results.     

Implementation of holonic scheduling and control in flow-line manufacturing systems: die-casting case study

The success of a flow-line manufacturing system depends on effective production scheduling and control. However, it has been found that current flow-line manufacturing scheduling and control algorithms lack the flexibility to handle interruptions or resource breakdowns; hence, system performance drops automatically and rapidly when interruptions occur. The objective of this research is to investigate if the performance of a flow-line manufacturing system can be improved by integrating agent-based, holonic scheduling and production control. A holonic manufacturing scheduling model has been developed and implemented into a die-casting manufacturing flow line throughout a simulation model. The analysis takes into account the comparisons of overall performances of the system models with the holonic scheduling and conventional scheduling approaches. Simulation results indicate that the holonic manufacturing scheduling and control can significantly increase the uptime efficiency and the production rate of the flow-line manufacturing system.     

Lampshade Game for lean manufacturing

The purpose of this article is to introduce a new simulation game named the ‘Lampshade Game’ that can be helpful in educating students and industry professionals on lean manufacturing principles. The Lampshade Game is an active learning tool that is capable of demonstrating the advantages and disadvantages of some of the key principles of lean manufacturing (such as quality focus, pull system, flexible manufacturing and visual organisation) in comparison to craft and mass manufacturing by manually simulating the production of lampshades for each of the process types. The game enables the comparison of these three manufacturing methods using different operational and financial metrics such as inventory levels, manufacturing cycle time, customer fill rate, production yield and cost and profit. This article describes the game, its objectives, and shares experiences from several classroom implementations including an analysis of pre- and post-surveys.     

Re-distributed manufacturing and the food-water-energy nexus: opportunities and challenges

Abstract

Addressing the intersection of two important emerging research areas, re-distributed manufacturing (RDM) and the food-energy-water (FEW) nexus, this work combines insights from engineering, business and policy perspectives and explores opportunities and challenges towards a more localized and sustainable food system. Analysis centred on two specific food products, namely bread and tomato paste reveals that the feasibility and potential of RDM vary with the type of food product and the supply chain (SC) components. Physically, energy efficiency, water consumption and reduction of waste and carbon footprint may be affected by scale and location of production activities and potentials of industrial symbiosis. From the business perspective, novel products, new markets and new business models are expected in order for food RDM to penetrate within the established food industry. Studies on policies, through the lens of public procurement, call for solid evidence of envisioned environmental, social and economic benefits of a more localized food system. An initial integrated framework is proposed for understanding and assessing food RDM and the FEW nexus.     

REDUTEX: a hybrid push–pull production system approach for reliable delivery time in knitting SMEs

The textile sector is composed of small and medium enterprises (SMEs) worldwide. Nowadays there is a shortage of technological knowledge in SMEs. Lead time is a critical indicator in any productive company organisation. The aim of this research was to provide an approach, called REDUTEX, based on theoretical concepts of lean and synchronous manufacturing in order to help to understand the behaviour of SMEs and to improve the manufacturing process by reducing the customer lead times. The integration of these philosophies is the basis of REDUTEX; a hybrid push–pull production system approach to knitting SMEs. With this approach, it is possible to obtain a process reliability when the restrictive resource capacity (RRC) is identified, optimised and protected. By synchronising all activities to the rhythm of RRC, through a continuous flow, it is possible to obtain high-impact results through a dual automated system and product quality, through a visual control. REDUTEX uses a push system from the RRC to the location of the supermarket, where accumulated inventory may be distributed in the internal assembly department and external family workshops, making a pull system. Subsequent re-assembly processes use a push system until the end of the product. The stages of REDUTEX are explicitly described and applied to real data, so that the staff of SMEs can easily understand the behaviour of the process and implement it. One of the advantages of REDUTEX is that it does not need highly trained staff. The research methodology was conducted as a case of study in twelve SMEs and validated and implemented in three textile companies of the southern area of the state of Guanajuato in Mexico, obtaining reliable delivery times and very promising results.     

生产性企业的概念性学习和操作性学习研究

本文用一个最优控制模型定量刻画了生产性企业计划期内的概念性学习和操作性学习与生产率、单位成本、废品率以及计划期内的总利润等生产经营指标之间的关系。模型的特点在于其能够规范地描绘众多变量之间的复杂关系。并简要阐述了由模型推导出的一些关于最优概念性学习和操作性学习策略的结论,详细分析了这些策略在生产性企业组织学习实践中的应用,获得了不同于传统理论的结果。     

Multi-echelon supply chain network design in agile manufacturing

In this paper, we consider a supply chain network design problem in an agile manufacturing scenario with multiple echelons and multiple periods under a situation where multiple customers have heavy demands. Decisions in our supply chain design problem include selection of one or more companies in each echelon, production, inventory, and transportation. We formulate the problem integrating all decisions to minimize the total operational costs including fixed alliance costs between two companies, production, raw material holding, finished products holding, and transportation costs under production and transportation capacity limits. A Lagrangian heuristic is proposed in this paper. Optimizing a Lagrangian relaxation problem provides a lower bound, while a feasible solution is generated by adjustment techniques based on the solution of subproblems at each iteration. Computational results indicate the high quality solutions with less than 5% optimality gap are provided quickly by the approach in this paper. Further, compared to initiative managerial alternatives, an improvement of 15% to 25% is not unusual in certain cases for the proposed approach.     

Redistributing food manufacturing: models for the creation and operation of responsive and agile production networks

Abstract

The food industry is a mature industry where its profit margins are thin and its R&D failure rate for new products is substantial. Both facts indicate that decent return on development investment cannot be provided and that the food industry cannot still rely on its traditional way of thinking and innovating. New product development cycles should involve not only the product itself but also the entire manufacturing and distribution network. Hence, collaborative manufacturing and servitization models are key elements for the rapid transformation of the new food industry. Moreover, recent developments in technology have the potential to shift manufacturing production away from large scale manufacturing plants to a network of distributed, smaller scale localized and customizable manufacturing facilities. Such a network is the crucial enabler for the on-demand manufacture of new or even, existing food products to rapidly respond to the consumers´ demands.     

生产性企业组织学习最优控制模型及其理论分析

运用最优控制理论研究生产性企业组织学习活动的动态最优决策问题.以企业的概念性学习投资率和操作性学习投资率为决策变量,累积知识量、生产率、单位成本和废品率等为状态变量,计划期内的总利润为指标函数,建立了一个最优控制模型,其特点在于规范地描绘概念性学习和操作性学习对企业累积知识量、生产率、单位成本、质量以及企业利润的动态影响.根据生产性企业组织学习和生产经营的实际情况,提出了一些定量化表达的假设和定义.在假设和定义的基础上利用最大值原理分析了所建立的模型,获得了关于动态最优概念性学习投资策略和操作性学习投资策略性质的一些结论,将这些结论与实际问题相结合,指出了在生产性企业组织学习实践上的含义.     

Joint modified block replacement and production/inventory control policy for a failure-prone manufacturing cell

This paper considers a joint preventive maintenance (PM) and production/inventory control policy of an unreliable single machine, mono-product manufacturing cell with stochastic non-negligible corrective and preventive delays. The production/inventory control policy, which is based on the hedging point policy (HPP), consists in building and maintaining a safety stock of finished products in order to respond to demand and to avoid shortages during maintenance actions. Without considering the impact of preventive and corrective actions on the overall performance of the production system, most authors working in the reliability and maintainability domains confirm that the age-based preventive maintenance policy (ARP) outperforms the classical block-replacement policy (BRP). In order to reduce wastage incurred by the classical BRP, we consider a modified block replacement policy (MBRP), which consists in canceling a preventive maintenance action if the time elapsed since the last maintenance action exceeds a specified time threshold. The main objective of this paper is to determine the joint optimal policy that minimizes the overall cost, which is composed of corrective and preventive maintenance costs as well as inventory holding and backlog costs. A simulation model mimicking the dynamic and stochastic behavior of the manufacturing cell, based on more realistic considerations of the real behavior of industrial manufacturing cells, is proposed. Based on simulation results, the joint optimal MBRP/HPP parameters are obtained through a numerical approach that combines design of experiment, analysis of variance and response surface methodologies. The joint optimal MBRP/HPP policy is compared to classical joint ARP/HPP and BRP/HPP optimal policies, and the results show that the proposed MBRP/HPP outperforms the latter. Sensitivity analyses are also carried out in order to confirm the superiority of the proposed MBRP/HPP, and it is observed that for practitioners, the proposed joint MBRP/HPP offers not only cost savings, but is also easy to manage, as compared to the ARP/HPP policy.     

Computer-aided formulation and optimal control of an integrated production system for competitive products

An integrated production, inventory and advertising system has been formulated based on control engineering principles. In this system, the customer's demand is satisfied from stock, which in turn is replenished from production facilities. But sales reflect the advertising effort, present as well as past. The past effort has been considered as a delay with an assumed delay period. The problem is formulated as a state and observation model. Out of this an augmented model of state and parameters is formed. The parameters describing the model are estimated from MAP discrete filter algorithm. It is shown that sales of product 1 or product 2 at (k + l)th period is effected by sales and advertising of product 1 or product 2 at the kth period, and also by sales and advertising of product 2 or product 1 at (k-θ)th period, where 6 is the delay.