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.     

Development of demand pull type control methods: The design of block action production control methods to reduce throughput time and improve supply chain synchronization

In this paper the implementation of time based manufacturing strategies and pull type control systems in an organization manufacturing electrical switchgear built to customers individual requirements are discussed in detail. The concept of block control to synchronize the production time of all internally and externally sourced components and materials is also introduced in an attempt to simplify production control methods and reduce throughput time. Savings in time and cost are described during a twenty months period of restructuring. Foundations were laid for a second objective which is an attempt to gain some linkage between throughput time reduction and resultant production costs.     

Supporting Quick Response Through Scheduling of Make-to-Stock Production/Inventory Systems*

Scheduling of traditional job shops in make-to-order systems has seen extensive research over the past three decades. In such systems, performance is often related to various job completion metrics such as average flow time, average lateness, etc. This paper examines a scheduling problem in a make-to-stock environment where individual job completion measures are irrelevant. In this case, customer orders are satisfied through on-hand inventory where customer service is more closely related to the manufacturer's ability to quickly satisfy demand. We consider the role of scheduling in reducing inventories and improving customer service in the context of a manufacturer who assembles several different products on a single assembly line. We develop scheduling rules for such a system and experimentally compare their performance to those typically used in such environments. Our results indicate that rules which consider the inventory position and demand forecast outperform traditional fixed cycle rules.     

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.     

Planned Lead Times in Multistage Systems

This study investigates the impact of planned lead times on performance in multistage manufacturing where material requirements planning is used in a make-to-stock environment. We simulate a variety of different operating environments and find: (1) planned lead times are important to customer service levels under all operating environments examined, but have a smaller impact on inventory investment; (2) tight due dates introduced by short planned lead times hurt customer service without saving much inventory; (3) small increases to tight planned lead times improve customer service substantially with small inventory increases; (4) co-component inventories change with planned lead times, and disparity between such inventories is a sign of poor timing coordination; (5) the fixed order quantity rule performs better than the periodic order quantity rule; and (6) tall product structure and large lot sizes require particular attention to planned lead times. The findings also extend the current understanding of planned lead times by including uncertainties such as forecast error, yield loss, and equipment reliability. The study concludes with a way to diagnose and improve poorly set planned lead times.     

A Comparison between Basic Cyclic Scheduling and Variable Cyclic Scheduling in a Two‐stage Hybrid Flow Shop

In this paper the impacts of two types of repetitive scheduling systems on the makespan in a two‐stage hybrid flow shop, which consists of one machine in the first stage and multiple process lines in the second stage, are compared. First, we analyzed, through a simulation, how the makespan is affected by the setup frequency and sequencing rules for products under two types of scheduling systems: One is repetitive scheduling with only one batch per product family per scheduling cycle (basic cyclic scheduling system). The other is repetitive cyclic scheduling with various batches per product family per scheduling cycle (variable cyclic scheduling system). Second, we compared which scheduling system is superior under various manufacturing situations. The following points were noted. (1) The superior scheduling system can be shown by a two‐dimensional diagram of the setup frequency and the imbalance in workload for processing among process lines in the second stage. (2) Variable cyclic scheduling is superior in comparison with basic cyclic scheduling when there is a large imbalance in the workload to be processed among process lines in the second stage, or the workload in the second stage is larger than that in the first stage. The result of this research provides guidelines for selecting which scheduling system should be adopted.     

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.     

Decentralized WIP-oriented manufacturing control (DEWIP)

DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.     

Design requirements for health care production control systems

This paper addresses the issue of determining design requirements for production control in health care organizations, with a restriction to the internal production control of hospitals. Hospital management has limited possibilities to control hospital production, as hospital production processes are driven by medical specialists who, however, do not manage that process. We consider therefore the hospital as a virtual organization, consisting of a number of relatively independent businesses in a common framework. Each business unit functions as a focused factory for a range of more or less homogeneous products. Production control principles can be applied to each of these businesses, but not to the system as a whole. A number of elements from classical production control theory can be also applied to health care, i.e. the use of decoupling points, the bottleneck-oriented approach, and the operational control between production and market. However, important factors that need to be considered in health production control are that often specifications on quality are not available at the start of the process, and that there is strong interaction between the patient and the process. Our conclusion is that a dedicated framework for approaching hospital production control is necessary. The specific characteristics of hospital care and its state of production control development are the main arguments for this dedicated framework.     

Information-Processing Alternatives for Coping with Manufacturing Environment Complexity

Investment in information systems and technology is often justified as a necessary strategy for coping with the increased complexity and information needs of today/s manufacturing environments. However, the world class manufacturing paradigm suggests that increased complexity is not always necessary to meet the needs of markets and customers. Galbraith/s (1973, 1977) seminal information-processing model is applied to a manufacturing environment, supported by the world class manufacturing paradigm, to test the role of various information-processing alternatives for coping with increased environmental complexity. Moderated regression and multiple discriminant analysis are used to test hypotheses in a sample of 164 manufacturing plants. Environmental complexity was found to be related to manufacturing performance for each of the five dependent variables. This relationship was moderated by at least one information-processing alternative for each dependent variable, including self-contained tasks, lateral relations, and environmental management strategies for reducing manufacturing, supplier, and goal diversity. Investments in information systems and reduction of labor and customer diversity did not moderate this relationship. Practices that were found to be particularly effective in moderating this relationship included the use of multifunctional employees, communication of manufacturing strategy, coordination of decision making, product design simplicity, reduction of parts counts, supervisory interaction facilitation, recruiting and selection for flexible employees, JIT practices, blanket purchase orders, and strong customer relationships.     

An integrated production and inventory model for a whole manufacturing supply chain involving reverse logistics with finite horizon period

This paper proposes a model and solution method for coordinating integrated production and inventory cycles in a whole manufacturing supply chain involving reverse logistics for multiple items with finite horizon period. A whole manufacturing supply chain involving reverse logistic consists of tier-2 suppliers supplying raw materials to tier-1 suppliers, tier-1 suppliers producing parts, a manufacturer which manufactures and assembles parts from tier-1 suppliers into finished products, distributors distributing finished products to retailers, retailers selling products to end customers and a third party which collects the used finished products from end customers, dissembles collected products into parts, and feed the parts back to the supply chain. In this system, we consider a finite horizon period. A mathematical model for representing the behaviors of the system is developed. Solution methods based on decentralized and a combination of decentralized and centralized decision making process, referred to as the semi-centralized decision making process, are proposed to solve the model while the centralized decision making process is solved by a mixed integer nonlinear programming method. A numerical example is used to demonstrate the model and the solutions based on the three types of the coordination.     

Economic Production Lot Sizing with Periodic Costs and Overtime*

Traditional approaches for modeling economic production lot‐sizing problems assume that a single, fixed equipment setup cost is incurred each time a product is run, regardless of the quantity manufactured. This permits multiple days of production from one production setup. In this paper, we extend the model to consider additional fixed charges, such as cleanup or inspection costs, that are associated with each time period's production. This manufacturing cost structure is common in the food, chemical, and pharmaceutical industries, where process equipment must be sanitized between item changeovers and at the end of each day's production. We propose two mathematical problem formulations and optimization algorithms. The models' unique features include regular time production constraints, a fixed charge for each time period's production, and the availability of overtime production capacity. Experimental results indicate the conditions under which our algorithms' performance is superior to traditional approaches. We also test the procedures on a set of lot‐sizing problems facing a national food processor and document their potential economic benefit.     

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.     

A Note on ‘An Approximate Solution to Deterministic Kanban Systems’: A Commentary and Further Insights

In a recent paper, Vemuganti, Batta, and Zhu (1996) stated that the linear programming model suggested by Moeeni and Chang (1990) could result in infeasibility. They also suggested an alternative mathematical formulation for determining the number of kanbans. The intention of this article is twofold. First, we maintain that the finding of Vemuganti et al., while valid, is based on a misplaced emphasis on the purpose of the Moeeni and Chang article. Second, we demonstrate that the Vemuganti et al. formulation is a special case of a more general model proposed by Bitran and Chang (1987).     

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.     

Simulation Analysis of a Manufacturing Supply Chain*

A supply chain is a series of manufacturing plants that transform raw material into finished product. A pipeline within a supply chain refers to the stream of information, material, components, and assemblies that are associated with a particular product. It is typical for manufacturing plants to put considerable effort to optimize the performance of a horizontal slice of a supply chain (such as coordination among parts that share a common resource). The need to optimize the performance of the vertical slice (the supply chain connecting raw material to finished product) by controlling the transmission of schedule instability and the resulting inventory fluctuation is often overlooked. A schedule is stable if actual production requirements for a given period do not change from the forecast production requirements. Stable production schedules are important when managing supply chains as they help control inventory fluctuation and inventory accumulation. Failure to control schedule instability results in high average inventory levels in the system. In this paper a simulation analysis of supply chain instability and inventory is conducted, and it is shown how supply chains can be analyzed for continuous improvement opportunities using simulation. The focus is on a stamping pipeline in an automobile supply chain based on operating data from General Motors (GM). It is shown that the techniques used in this paper are a useful tool for supply chain analysis.     

Design and implementation of an integrated production planning system for a pharmaceutical manufacturing concern in India

SmithKline Beecham (SBPI) is a major player in the Indian pharmaceutical industry. Though relatively small in terms of turnover, it has performed Pharmaceuticals (India) exceptionally well in terms ofprofitability and growth rate. The firm has substantial cash reserves. However, the firm operates in 'mass production' mode at present, with the established finished goods inventory norms being in the range of 1 to 1.5 months. Competitive pressure on the firm is now forcing it to move towards world class manufacturing and the application of concepts from MRP II, JIT and OPT is under consideration. This paper describes the considerations that went into the justification, design and implementation of an integrated production planning and control system in this situaion.     

The Value of Using Scheduling Information in Planning Material Requirements*

Current research and practice in the field of production and inventory planning is dominated by hierarchical, material requirements planning-based methods. The objective of this research is to determine the merits of a major redirection for the design of manufacturing planning systems—a direction that more directly exploits the capabilities of modern computer technology. We test the relative performance of two fundamentally different classes of manufacturing planning systems: (1) those that make no use of sequencing and scheduling information in the planning of material deliveries (for example, traditional MRP-based systems), and (2) those that use sequencing and scheduling information to plan delivery of materials. We first derive an analytical expression for the expected benefit (in terms of flow time reduction) of using scheduling information for a single machine system. We then describe and test a simple heuristic for predicting the improvement that could be realized in more complicated multimachine systems, under certain conditions. Results from controlled simulation experiments, over a wide range of operating environments, suggest that although the value of scheduling information is influenced by the operating environment, it could be substantial.     

A survey of simulation modeling techniques in production planning and control (PPC)

The manufacturing sector as a whole has undergone remarkable changes in terms of scale, complexity and technology over the past decades and this applies across most modern high-technology manufacturing such as electronics, semiconductor, aerospace and automotive industries. In order to remain competitive, manufacturers have to produce high-quality products at low cost, and at the same time retain sufficient flexibility and to meet rapidly changing customer demands. Production planning and control (PPC) is a key role which enables the manufacturer to gain visibility and control over all aspects of manufacturing activities. PPC in itself forms a subject of study, within which simulation techniques have proven themselves to be one of the most practical methodologies available to investigate and evaluate manufacturing issues. In this review paper, we focus on state-of-the art applications of simulation techniques in PPC to demonstrate their applicability to modern manufacturing issues. The review reports on academic publications on simulation applications in manufacturing from 2002 to 2014, incorporating surveys of peer-reviewed literature. The review covers three types of simulation techniques (system dynamic, discrete event simulation and agent-based simulation) and eight PPC issues (facility resource planning, capacity planning, job planning, process planning, scheduling, inventory management, production and process design, purchase and supply management). Literature survey is analysed on the basis of simulation application to PPC problems which can give a guideline for simulation technique selection and also can help for simulation modelling in PPC problemsWould you consider changing the term “modeling” to “modelling” in the title. Please check, and correct if necessary.