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.     

Changes in production control required for untended operation of a flexible manufacturing cell

This article examines and improves the production control system of a firm that wants to operate its flexible manufacturing cell (FMC) in an untended third shift. The FMC consists of a machining centre, a pallet storage, a rail-guided transport vehicle for pallets and a clamping/unclamping station. The current production control system of the firm shows several deficiencies with respect to operating the FMC efficiently. This article proposes changes in the current production control hierarchy and introduces some new methods to solve major production control problems. The study illustrates the interaction between quantitative tools, organisational decisions and behavioural considerations. The approaches are general and can be used in other environments.     

Production planning in a MRP/JIT repetitive manufacturing environment

Some literature suggests that the best approach to production planning is a complete implementation of just-in-time. It has also been suggested that JIT replaces material requirements planning, and computerized procedures are an unnecessary complex burden on management especially in a highly repetitive environment. This article examines the JIT programme at the John Deere Engine factory. In 1985 the factory began a JIT programme with the belief that it would replace their MRP system. The results of the JIT programme are examined and management's conclusion that the best approach is a blend of JIT and MRP is explored.     

Integration of process planning and production planning and control in cellular manufacturing

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.     

A review of hierarchical production planning and its applicability for modern manufacturing

The hierarchical production planning (HPP) paradigm has become an accepted planning and control strategy for many medium-to-large manufacturing situations. While the paradigm appears intuitively obvious and appropriate for many factories, there are a number of modern manufacturing situations where the application of the HPP approach may not be appropriate. By understanding the fundamental principles and concepts inherent in the HPP approach, it is possible to identify situations suitable for HPP with little or no adaptation, and situations where HPP must be extensively modified before use. A poor understanding of HPP     

Dynamic scheduling of manufacturing job shops using extreme value theory

Most job shop scheduling approaches reported in the literature assume that the scheduling problem is static (i.e. job arrivals and the breakdowns of machines are neglected) and in addition, these scheduling approaches may not address multiple criteria scheduling or accommodate alternate resources to process a job operation. In this paper, a scheduling method based on extreme value theory (SEVAT) is developed and addresses all the shortcomings mentioned above. The SEVAT approach creates a statistical profile of schedules through random sampling, and predicts the quality or 'potential' of a feasible schedule. A dynamic scheduling problem was designed to reflect a real job shop scheduling environment closely. Two performance measures, viz. mean job tardiness and mean job cost, were used to demonstrate multiple criteria scheduling. Three factors were identified, and varied between two levels each, thereby spanning a varied job shop environment. The results of this extensive simulation study show that the SEVAT scheduling approach produces a better performance compared to several common dispatching rules.     

A possibilistic aggregate production planning model for brass casting industry

This article discusses a possibilistic aggregate production planning (APP) model for blending problem in a brass factory; the problem computing optimal amounts of raw materials for the total production of several types of brass in a planning period. The model basically has a multi-blend model formulation in which demand quantities, percentages of the ingredient in some raw materials, cost coefficients, minimum and maximum procurement amounts are all imprecise and have triangular possibility distributions. A mathematical model and a solution algorithm are proposed for solving this model. In the proposed model, the Lai and Hwang's fuzzy ranking concept is relaxed by using ‘Either-or’ constraints. An application of the brass casting APP model to a brass factory demonstrates that the proposed model successfully solves the multi-blend problem for brass casting and determines the optimal raw material purchasing policies.     

A framework for production rescheduling in sociotechnical manufacturing environments

No plan survives contact with reality. Despite the rich research base regarding handling uncertainty in production planning and control systems, there is an intellectual gap between theory and practice with regard to handling unforeseen events generated by internal and external factors, such as unforeseen machine downtimes and changes in demand. Motivated by longitudinal observations in two industrial settings and an analysis of the relevant literature, a framework for rescheduling decision-making in the face of unforeseen production events is proposed. In practical settings, the effectiveness of decisions depends on a set of situational factors. The findings of this research can be utilised further to provide guidelines for developing effective decision support principles and systems, addressing the needs of organisational decision-makers.     

Time window capacity analysis for synchronous production

Synchronous production is a philosophy that suggests that the right part should arrive at the right machine at the right time to minimize the inventory and operating costs. To achieve this goal a synchronous material flow is required. How ever, this is not an easy task in the discrete manufacturing environment because it requires management commitment and algorithmic development. This paper proposes a time window capacity analysis (TWCA) approach to implement the synchronous production. By dividing the production time into small time windows, simple rules, heuristics and algorithms are developed to assign operations among available resources such that the inventory and operating costs are kept low. The synchronization is achieved by resolving the demands of each operation in the order of time windows. The approach is simple and has been implemented and tested in an actual manufacturing company. The results show that TWCA is practical and promising. TWCA has the potential to be used in either single, multiple, or parallel machines, one stage or multi-stage, job shops or flow shops, and closed or open systems.     

2MTO,a new mapping tool to achieve lean benefits in high-variety low-volume job shops

This paper proposes the ‘Mapping Tool for Make-To-Order companies’ (2MTO), a new approach to map, analyse and achieve lean benefits in high-variety-low-volume job shops. The focus is, mainly, on the transitional phase from push to pull, when there is a compelling need to acquire a deep understanding of the current state of the system under analysis. Sometimes, in this initial phase, a pure pull approach cannot be developed and a job shop configuration must be maintained. If so, 2MTO allows selecting a suitable hybrid Production Planning and Control system to control Work-In-Process and to limit lead times, so as to quickly achieve lean benefits, without significantly altering the original layout. 2MTO is fully explained making reference to an Italian precision mechanic company, where the application of the method led to a successful implementation of a Workload Control system.     

A simulation testing and analysis of aggregate production planning strategies

In this study, a hybrid discrete event simulation (DES) and system dynamics (SD) methodology is applied to model and simulate aggregate production planning (APP) problem for the first time. DES is used to simulate operational-level and shop-floor activities incorporated into APP and estimate critical time-based control parameters used in SD model of APP and SD is used to simulate APP as a collection of aggregate-level strategic decisions. The main objective of this study is to determine and analyse the effectiveness of APP strategies regarding the Total Profit criterion by developing a hybrid DES–SD simulation model for APP in a real-world manufacturing company. The simulation results demonstrated that the priority of APP strategies with regards to Total Profit criterion is: (1) the pure chase strategy, (2) the modified chase strategy, (3) the pure level strategy, (4) the modified level strategy, (5) the mixed strategy and (6) the demand management strategy, respectively. The APP system is first simulated under mixed strategy (basic scenario) conditions to include all APP capacity and demand options in constructed SD simulation model to show a comprehensive view of APP components and their interdependent interactions. Then, the obtained results will be used as Total Profit measure to compare with system's performance under some experimental scenarios applying different APP strategies.     

Freezing the master production schedule in multilevel material requirements planning systems under deterministic demand

This paper extends the studies by Sridharan, Berry, and Udayabhanu from single-level MPS systems to multilevel material requirements planning (MRP) systems, and examines the impact of product structure, lot-sizing rules and cost parameters upon the selection of MPS freezing parameters under deterministic demand. A model is built to simulate the master production scheduling and material requirements planning operations in a make-to-order environment. The results show that all the MPS freezing parameters studied have a significant impact upon total inventory costs and schedule instability in multilevel MRP systems. First, the order-based freezing method is preferable to the period-based method. Secondly, the study finds that increasing the freezing proportion reduces both total inventory costs and schedule instability. This finding contradicts the finding by Sridharan et al. in single-level systems. Thirdly, the study finds that a higher replanning periodicity results in both lower total inventory cost and lower schedule instability. The study also indicates that the product structure and lot-sizing rules do not significantly influence the selection of MPS freezing parameters in a practical sense under most situations. However, the cost parameter seems to significantly influence the selection of replanning periodicity.     

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.     

Experimental push/pull production planning and control system

We introduce an experimental push/ pull production planning and control software system which is designed as an alternative to a MRP-II system for mass manufacturing enterprises in China. It has the following distinguishing features: (1) putting the philosophy of JIT into the master production scheduling of MRP-II via the earliness/ tardiness production planning method; (2) controlling material input by push and processing/ assembly by pull; and (3) adjusting the parameters of the production line by the‘ suggestion for improvement of production line’ module. Simulation results have shown that the proposed system can achieve better planning and control performance than existing systems.     

A hierarchical production plan for a make-to-order steel fabrication plant

A three-tiered hierarchical production plan (HPP) for a strictly make-to-order steel fabrication plant with the objective of developing a production plan and master schedule for a set of product archetypes is implemented. Data are collected from an actual steel fabrication plant located in the Midwestern section of the US. An aggregate linear programming model, a non-linear disaggregate model and a master production schedule comprise the respective tiers. Appropriate models provide the forecasts needed in the first two tiers. A production plan and master schedule based on data collected at the plant, benefits expected for its implementation and practical limitations are reported.     

多品种集约生产计划问题的模糊方法

提出具有模糊需求量和模糊能力约束以及资本水平约束的多品种类集约生产计划问题 的模糊优化模型及模糊解方法. 通过对模糊需求量和模糊等式的描述,提出了模糊需求环境下 生产- 库存平衡方程的两种等价的描述方法, 并给出了模糊等式的实用解释. 建立了具有模 糊需求量和模糊能力约束集约生产计划问题的优化模型FMAPP ,并给出了求解模型的参数规 划方法.     

Managing key interfaces in production planning and control

Detailed observational research, undertaken in two large and complex manufacturing businesses, identified ways in which work groups interface to employ knowledge to perform production planning and control activities. Eleven interfaces were observed and methods were established to classify them into types based on how knowledge is communicated and shared. Characteristics of the decision-making environment on either side of each interface were identified to explore their impact on interface type. Key differences in decision-makers’ predominant modes of decision-making, their agendas, and the form and scope of their knowledge were found to influence communication and decision-making processes. These findings have implications for production planning and control organisation and process design. In particular, it is seen that the effectiveness of interfaces may be improved through the alignment of decision-making approaches, agendas and knowledge across interfaces and/or through the effective use of interface tools that enable decision-makers to understand the consequences of decisions made.     

基于投产点库存的随机综合生产计划模型研究

以企业基于投产点法的生产与库存控制策略为研究起点,分析了随机需求条件下生产系统服务水平与库存水平的数量关系,并将产品在计划期间的平均库存量引入综合生产计划模型。模型中计划期产量是与产品需求具有相同分布的随机变量,模型的优化目标是通过确定最佳的投产库存量和生产系统服务水平,求得相应的计划期产量区间。提出了模型的计算机辅助求解算法,并采用案例分析验证了模型的有效性。     

能力与资源双重约束下的启发式组合生产计划研究

企业面向市场的产品交付能力,一般受约束于各制造环节的生产能力,而各制造环节的生产能力又受约束于其可得的制造资源。研究了在局部生产能力具有上限,且总体制造资源受约束的情况下,如何制定生产计划,以使总体利润最大的问题。建立了基于能力和资源双重约束下的生产计划组合优化模型,设计了一种"双线退火"的模拟退火算法,来启发式求解此类连续变量组合优化问题,并以大量算例计算验证了双线模拟退火算法的效率和正确性。最后结合某耐火材料企业进行了应用分析研究,展示了模型的应用原理和算法的求解效果。