Enterprise Resource Planning (ERP) Competence Constructs: Two‐Stage Multi‐Item Scale Development and Validation*

This paper defines and operationalizes eight ERP competence constructs. We define ERP competence as a portfolio of managerial, technical and organizational skills and expertise posited as antecedents to improved business performance occurring after an ERP system is operational and functionally stable. To improve responses to changes in markets and products, manufacturers are increasingly adopting ERP systems. However, anecdotal accounts indicate that the realization of ERP's potential benefits is rare. Because of its pervasive influence on manufacturing and business performance, the need for scientifically developed and tested multi‐item scales pertaining to ERP competence is highly relevant to manufacturing strategy research. We follow a two‐stage normative process of scale development. First, we identify a portfolio of eight generic constructs that are hypothesized to be associated with successful ERP adoption. Each construct is then operationalized as a multi‐item measurement scale by applying a manual item sorting technique iteratively to independent panels of expert judges until tentative reliability and validity is established. Second, we further refine and validate the multi‐item scales using survey data from 79 North American manufacturing users of ERP systems.     

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.     

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.     

Design of Stockless Production Systems

In make‐to‐stock production systems finished goods are produced in anticipation of demand. By contrast, in stockless production systems finished goods are not produced until demand is observed. In this study we investigate the problem of designing a multi‐item manufacturing system, where there is both demand‐ and production‐related uncertainty, so that stockless operation will be optimal for all items. For the problem of interest, we focus on gaining an understanding of the effect of two design variables: (i) manufacturing speed—measured by the average manufacturing rate or, equivalently, the average unit manufacturing time, and (ii) manufacturing consistency—measured by the variation in unit manufacturing times. We establish conditions on these two variables that decision makers can use to design stockless production systems. Managerial implications of the conditions are also discussed.     

Multistage Stochastic Optimization for Production‐Inventory Planning with Intermittent Renewable Energy

A growing number of companies install wind and solar generators in their energy‐intensive facilities to attain low‐carbon manufacturing operations. However, there is a lack of methodological studies on operating large manufacturing facilities with intermittent power. This study presents a multi‐period, production‐inventory planning model in a multi‐plant manufacturing system powered with onsite and grid renewable energy. Our goal is to determine the production quantity, the stock level, and the renewable energy supply in each period such that the aggregate production cost (including energy) is minimized. We tackle this complex decision problem in three steps. First, we present a deterministic planning model to attain the desired green energy penetration level. Next, the deterministic model is extended to a multistage stochastic optimization model taking into account the uncertainties of renewables. Finally, we develop an efficient modified Benders decomposition algorithm to search for the optimal production schedule using a scenario tree. Numerical experiments are carried out to verify and validate the model integrity, and the potential of realizing high‐level renewables penetration in large manufacturing system is discussed and justified.     

NEW TECHNOLOGY INVESTMENTS IN MULTISTAGE PRODUCTION SYSTEMS

The introduction of new technologies in production and manufacturing (such as robotics, flexible manufacturing systems (FMS), and computer-aided design and manufacturing (CAD/CAM)) frequently motivates capital investment decisions. Traditionally, the need for additional capacity has motivated the evaluation of investment decisions which were undertaken based on financial factors such as the net present value (NPV), internal rate of return, taxation, and depreciation. This research integrates investment decisions with operational decisions for the case of multistage production assembly systems. We show that for such systems investment decisions affect not only the financial structure but also production scheduling and material flow in the system.     

Expert Judgment in Risk Analysis and Management: Process, Context, and Pitfalls

The regulation and management of hazardous industrial activities increasingly rely on formal expert judgment processes to provide wisdom in areas of science and technology where traditional "good science" is, in practice, unable to supply unambiguous "facts." Expert judgment has always played a significant, if often unrecognized, role in analysis; however, recent trends are to make it formal, explicit, and documented so it can be identified and reviewed by others. We propose four categories of expert judgment and present three case studies which illustrate some of the pitfalls commonly encountered in its use. We conclude that there will be an expanding policy role for formal expert judgment and that the openness, transparency, and documentation that it requires have implications for enhanced public involvement in scientific and technical affairs.     

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.     

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.     

An aggregate production planning framework for the evaluation of volume flexibility

Flexibility in manufacturing has been identified as one of the key factors to success in the marketplace. Many types of flexibility have been identified in the literature among which volume flexibility is one of the most important. Volume flexibility of a manufacturing system is defined as its ability to be operated profitably at different overall output levels. Volume flexibility permits a manufacturing system to adjust production upwards or downwards within wide limits. In this paper, we develop an aggregate production planning model for volumeflexible production systems. The model can be used with a Monte Carlo simulation to evaluate the optimal level of investment in volume flexibility for a firm operating under a given set of market conditions. In addition, the model can be used to develop some conclusions about the relationship between the value of volume flexibility and the cost of holding inventory, the cost of shortage, forecast accuracy, and the length of the planning horizon.     

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.     

A model for integrated production-packaging systems

The problem of determining the economic packaging frequency of jointly replenished items has received a lot of attention from researchers. This problem is usually encountered while packaging the products after completing manufacture. Nevertheless, production batch quantities certainly influence the manufacturing cycle time of products and hence the economic packaging quantities for jointly replenished items. Therefore, realizing the importance of the relationship between production batch quantities and packaging quantities     

The Impact of Contract Manufacturing on Inventory Performance: An Examination of U.S. Manufacturing Industries

In recent years, a growing number of original equipment manufacturers (OEMs) have transferred their manufacturing processes to specialized firms, known as contract manufacturers. In so doing, contract manufacturers can reduce an OEM's production costs and provide OEMs with flexibility in the production process. We examine another potential reason for the use of contract manufacturing—the potential for efficiency gains from inventory reductions. Employing econometric models and data representing manufacturing industries in the USA, we provide statistical evidence that contract manufacturing can lead to lower industry‐wide inventory levels, after controlling for other relevant factors. Key managerial implications are derived from the analysis.     

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。     

Lowest Cost May Not Lower Total Cost: Using “Spackling” to Smooth Mass‐Customized Production

Consider a manufacturer who mass customizes variants of a product in make‐to‐order fashion, and also produces standard variants as make‐to‐stock. A traditional manufacturing strategy would be to employ two separate manufacturing facilities: a flexible plant for mass‐customized items and an efficient plant for standard items. We contrast this traditional focus strategy with an alternative that better utilizes capacity by combining production of mass‐customized and standard items in one of two alternate spackling strategies: (1) a pure‐spackling strategy, where the manufacturer produces everything in a (single) flexible plant, first manufacturing custom products as demanded each period, and then filling in the production schedule with make‐to‐stock output of standard products; or (2) a layered‐spackling strategy, which uses an efficient plant to make a portion of its standard items and a separate flexible plant where it spackles. We identify the optimal production strategy considering the tradeoff between the cost premium for flexible (versus efficient) production capacity and the opportunity costs of idle capacity. Spackling amortizes fixed costs of capacity more effectively and thus can increase profits from mass customization vis‐à‐vis a focus strategy, even with higher cost production for the standard goods. We illustrate our framework with data from a messenger bag manufacturer.     

制造系统生产单元碳排放核算模型

制造业是我国国民经济的支柱产业，但也是环境污染物排放的主要来源、能源消耗主体和温室气体排放大户。制造系统高能耗、高物耗、高碳排放的加工过程是造成制造业碳排放量大的重要原因。生产单元作为制造系统的加工的主体，其碳排放量的核算是确定整个制造系统乃至制造业碳排放总量的关键。本文首先对生产单元的原材料、电能、辅助物料及废屑处理所引起的碳排放进行分析，确定生产单元的碳排放源；其次，产品合格率的不同会造成生产单元输入及输出的成品/半成品数量的差异，进而影响生产单元单位产品的碳排放量，在此基础上，综合考虑了原材料、电能、辅助物料及废屑处理的碳排放情况，构建了给定工艺流程下生产单元碳排放核算模型。最后，结合一汽车排气装置加工实例，分别核算加工过程中九个生产单元的碳排放量，验证了模型的可行性。     

MANUFACTURING PROCESS TECHNOLOGY and SUPPORT STAFF COMPOSITION: AN EMPIRICAL VIEW OF INDUSTRY EVIDENCE

Despite the attention given to restructuring and trimming down manufacturing firms during the 198Os, little attention has been paid to the mix of skills they needed under different circumstances. We examined the patterns of employment by occupation in manufacturing industries utilizing different production technologies and the effect of establishment size on nonproduction employment. We found that a relationship exists between production technology and nonproduction employment per 100 production workers. Establishment size is found to be a moderator between nonproduction employment and production technology. Our findings imply two clear messages for managers. First, when considering major changes in production technology, managers should be aware that the supporting skills they will need from their nonproduction work force are likely to change greatly. Further, these changes involve technical and managerial workers as well as clerical and production support people. Second, they should restructure the functional or occupational mix of an organization in the context of the process technologies in place. Different process technologies require different structures.     

CAPACITY AND PRODUCTION DECISIONS IN STOCHASTIC MANUFACTURING SYSTEMS: AN ASYMPTOTIC OPTIMAL HIERARCHICAL APPROACH

We present a new paradigm of hierarchical decision making in production planning and capacity expansion problems under uncertainty. We show that under reasonable assumptions, the strategic level management can base the capacity decision on aggregated information from the shopfloor, and the operational level management, given this decision, can derive a production plan for the system, without too large a loss in optimality when compared to simultaneous determination of optimal capacity and production decisions. The results are obtained via an asymptotic analysis of a manufacturing system with convex costs, constant demand, and with machines subject to random breakdown and repair. The decision variables are purchase time of a new machine at a given fixed cost and production plans before and after the purchase. The objective is to minimize the discounted costs of investment, production, inventories, and backlogs. If the rate of change in machine states such as up and down is assumed to be much larger than the rate of discounting costs, one obtains a simpler limiting problem in which the random capacity is replaced by its mean. We develop methods for constructing asymptotically optimal decisions for the original problem from the optimal decisions for the limiting problem. We obtain error estimates for these constructed decisions.     

Dynamic performance of a hybrid inventory system with a Kanban policy in remanufacturing process

In this paper we study a hybrid system with both manufacturing and remanufacturing. The inventory control strategy we use in the manufacturing loop is an automatic pipeline, inventory and order based production control system (APIOBPCS). In the remanufacturing loop we employ a Kanban policy to represent a typical pull system. The methodology adopted uses control theory and simulation. The aim of the research is to analyse the dynamic (as distinct from the static) performance of the specified hybrid system. Dynamics have implications on total costs in terms of inventory holding, capacity utilisation and customer service failures. We analyse the parameter settings to find preferred “nominal”, “fast” and “slow” values in terms of system dynamics performance criteria such as rise time, settling time and overshoot. Based on these parameter settings, we investigate the robustness of the system to changes in return yield and the manufacturing/remanufacturing lead time. Our results clearly show that the system is robust with respect to the system dynamics performance and the remanufacturing process can help to improve system dynamics performance. Thus, the perceived benefits of remanufacturing of products, both environmentally and economically, as quoted in the literature are found not to be detrimental to system dynamics performance when a Kanban policy is used to control the remanufacturing process.