Production planning in practice

The changes and pressures facing the manufacturing and engineering industries today are increasing the importance of effective aggregate manpower and production planning. Several different theoretical optimisation models to tackle this problem have been described in detail in the literature but there have been few applications of them in practice.The reasons for this are many but include: the difficulty in expressing managements' conflicting and mixed objectives in an objective function; the necessity to oversimplify real life systems to enable these methods to be used; the simplistic approach to manpower planning used in these models; the difficulty in gaining managements' acceptance and finally the fact that what management actually wants is a tool to assist them in planning and decision making.What is being used by many managements is a case-study deterministic simulation model. Many companies are adopting this type of model for all types of planning and twelve out of twenty-seven companies visited in a research project described in this paper were using this type of model for aggregate manpower and production planning. It is proving to be an effective management tool and is being readily accepted principally because modern specialised financial modelling languages are enabling these models to be built, understood and used by non-specialist managers.     

Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations

The main purpose of this research is to develop and deploy an analytical framework for measuring the environmental performance of manufacturing supply chains. This work's theoretical bases combine and reconcile three major areas: supply chain management, environmental management and performance measurement. Researchers have suggested many empirical criteria for green supply chain (GSC) performance measurement and proposed both qualitative and quantitative frameworks. However, these are mainly operational in nature and specific to the focal company. This research develops an innovative GSC performance measurement framework by integrating supply chain processes (supplier relationship management, internal supply chain management and customer relationship management) with organisational decision levels (both strategic and operational). Environmental planning, environmental auditing, management commitment, environmental performance, economic performance and operational performance are the key level constructs. The proposed framework is then applied to three selected manufacturing organisations in the UK. Their GSC performance is measured and benchmarked by using the analytic hierarchy process (AHP), a multiple-attribute decision-making technique. The AHP-based framework offers an effective way to measure and benchmark organisations’ GSC performance. This study has both theoretical and practical implications. Theoretically it contributes holistic constructs for designing a GSC and managing it for sustainability; and practically it helps industry practitioners to measure and improve the environmental performance of their supply chain.     

Supply chain relationship quality and its impact on firm performance

Abstract

This paper examines the impact of supply chain relationship quality (SCRQ) on firm performance (FP) through the mediators of supply chain management processes (SCMP) and supply chain performance (SCP). In the literature, these linkages have been examined separately; in contrast, this study takes a holistic perspective on the antecedents of FP. The model was tested using survey data from manufacturing companies. Variance-based structural equation modelling revealed that both SCMP and SCP lead to FP, unlike SCRQ. On the other hand, SCRQ affects SCMP. Drawing on the resource-based view, consistency in SCRQ can lead to not only efficient and effective supply chain management but also improvements in FP and SCP. This research has practical implications, providing supply chain decision makers with insights on enhancing FP. Supply chain decision makers will be able to benefit from the findings of our study by improving supply chain relationships with supply chain members and ensuring FP. This research also highlights how effective management of SCRQ, SCMP and SCP can provide better FP and a competitive advantage.     

Optimal Acquisition of FMS Technology Subject to Technological Progress*

In order to gain competitive advantage, a firm must link its technology choice to its total manufacturing strategy and business unit's goals. A dynamic model is presented to examine the strategic decision concerning the acquisition of flexible manufacturing systems (FMS) technology. A major contribution of this model is its ability to capture the strategic benefits of FMS with respect to economies of scope and technological progress. Decisions such as the timing and size of new technology acquisition and the scrapping of conventional capacity are explored as a firm plans for the upgrading of its facility to meet future dynamic strategic goals. This model may be used to assist with strategic planning because it identifies the critical relationships and trade-offs between various exogenous forces (such as market growth or decay, the cost of acquiring flexible manufacturing systems, and the rate of technological progress) and the decision variables considered.     

三级装备制造业供应链质量管理行为研究

作为我国工业化建设和国民经济发展的根本保证,供应链环境下装备制造企业的产品质量问题受到了广泛关注。本文重点考虑产品质量对供应链收益的影响,运用微分对策理论研究由单一制造商、单一部件供应商和单一零件供应商构成的三级装备制造业供应链质量管理行为的协调问题。通过对比Nash非合作博弈和Stackelberg主从博弈两种分散式决策模式及集中式决策模式下协同合作博弈的均衡结果,得到相关结论,并利用算例进行验证。研究表明,①分散式决策下,制造商的质量管理行为相同,但相比于Nash非合作博弈,Stackelberg主从博弈能够改善部件供应商和零件供应商的质量管理行为,提升供应链成员的收益水平;②集中式决策下,供应链成员的质量管理行为达到最优,系统整体收益实现最大。研究结论为装备制造业供应链成员间质量管理战略联盟的构建提供了理论依据。     

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.     

A Microeconomic Model of the Focused Factory-Vertical Integration Strategic Decision Problem

The design of a manufacturing strategy incorporates the decision of whether to focus or vertically integrate, or adopt a policy somewhere between the two extremes. Unfortunately, the literature contains few models that aid a manager in this decision process. In this paper we design a model to evaluate and compare various strategic alternatives along the focused factory-vertical integration continuum. By defining a point along this continuum as the percent of components manufactured internally that are needed to make one finished item (where 0 indicates complete focus and one manufacturing step, and 1 indicates full integration and 100 percent internal manufacturing) we are able to delineate the effects of the alternative decision strategies on flexibility and the firm's cash flow. The capital asset pricing model is invoked to assess the impact on the firm's risk and value.     

Product universality and design for supply chain management

We describe our experience of developing models in which the principles of design for supply chain management (DFCM) have been implemented for new product development at Hewlett-Packard Company (HP). This experience arises from the development of a new product that is scheduled to be released in 1995. A key design decision faced by the product development team was whether to use a universal module or regionally dedicated modules to satisfy global market requirements. We describe a wide range of factors—including manufacturing and logistics costs—that could be used to support the design decision; these factors associated with product and process design contribute to tolal supply chain costs. We review the analytical model used to evaluate the cost and service implications of the two design alternatives. Finally, we discuss qualitative considerations that might influence the eventual decisions as well as the lessons learned from this real world experience.     

Optimal Dynamic Pricing of Perishable Items by a Monopolist Facing Strategic Consumers

We introduce a dynamic pricing model for a monopolistic company selling a perishable product to a finite population of strategic consumers (customers who are aware that pricing is dynamic and may time their purchases strategically). This problem is modeled as a stochastic dynamic game in which the company's objective is to maximize total expected revenues, and each customer maximizes the expected present value of utility. We prove the existence of a unique subgame‐perfect equilibrium pricing policy, provide equilibrium optimality conditions for both customer and seller, and prove monotonicity results for special cases. We demonstrate through numerical examples that a company that ignores strategic consumer behavior may receive much lower total revenues than one that uses the strategic equilibrium pricing policy. We also show that, when the initial capacity is a decision variable, it can be used together with the appropriate pricing policy to effectively reduce the impact of strategic consumer behavior. The proposed model is computationally tractable for problems of realistic size.     

Branch‐and‐Price Methods for Prescribing Profitable Upgrades of High‐Technology Products with Stochastic Demands*

This paper develops a model that can be used as a decision support aid, helping manufacturers make profitable decisions in upgrading the features of a family of high‐technology products over its life cycle. The model integrates various organizations in the enterprise: product design, marketing, manufacturing, production planning, and supply chain management. Customer demand is assumed random and this uncertainty is addressed using scenario analysis. A branch‐and‐price (B&P) solution approach is devised to optimize the stochastic problem effectively. Sets of random instances are generated to evaluate the effectiveness of our solution approach in comparison with that of commercial software on the basis of run time. Computational results indicate that our approach outperforms commercial software on all of our test problems and is capable of solving practical problems in reasonable run time. We present several examples to demonstrate how managers can use our models to answer “what if” questions.     

Decision Making with Uncertain Judgments: A Stochastic Formulation of the Analytic Hierarchy Process*

In the analytic hierarchy process (AHP), priorities are derived via a deterministic method, the eigenvalue decomposition. However, judgments may be subject to error. A stochastic characterization of the pairwise comparison judgment task is provided and statistical models are introduced for deriving the underlying priorities. Specifically, a weighted hierarchical multinomial logit model is used to obtain the priorities. Inference is then conducted from the Bayesian viewpoint using Markov chain Monte Carlo methods. The stochastic methods are found to give results that are congruent with those of the eigenvector method in matrices of different sizes and different levels of inconsistency. Moreover, inferential statements can be made about the priorities when the stochastic approach is adopted, and these statements may be of considerable value to a decision maker. The methods described are fully compatible with judgments from the standard version of AHP and can be used to construct a stochastic formulation of it.     

Some trends in corporate modelling

This paper reviews the evidence of a number of surveys and case studies of corporate modelling in the U.K. Some general conclusions as to trends are drawn. Thus corporate models will display increasing modularity; will be more likely to include probabilistic elements; will more often incorporate physical flows; and will be generally linked to a greater number of other models in organisations. Micros are making a substantial impact as tools for running decision support systems both of the corporate model and the ad hoc model variety. Forecasting techniques are still greatly underutilised in many organisations. Although most corporate models are currently of the deterministic financial simulation type, the influence of management education will help the adoption of more advanced models by more numerate senior managers and accountants. Indeed there is already evidence that this is happening in some organisations.     

Quality management and performance: a comparison between the UK and Turkey

Purpose: The aim of this article is to detail the correlation between quality management, specifically its tools and critical success factors, and performance in terms of primary operational and secondary organisational performances.

Design/methodology/approach: Survey data from the UK and Turkey were analysed using exploratory factor analyses, structural equation modelling and regression analysis.

Findings: The results show that quality management has a significant and positive impact on both primary and secondary performances; that Turkish and UK attitudes to quality management are similar; and that quality management is widely practised in manufacturing and service industries but has more statistical emphasis in the manufacturing sector. The main challenge for making quality management practice more effective lies in an appropriate balanced use of the different sorts of the tools and critical success factors.

Originality/value: This study takes a novel approach by: (i) exploring the relationship between primary operational and secondary organisational performances, (ii) using service and manufacturing data and (iii) making a cross-country comparison between the UK (a developed economy) and Turkey (a developing economy).

Limitations: Detailed contrast provided between only two countries.     

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.     

A chance-constraints linear programming model on the economic evaluation of flexible manufacturing systems

The implementation of flexible manufacturing systems (FMSs) normally entails a large initial investment under a long-term, uncertain environment. Many effects of installing a FMS will be due to improvement in throughput efficiency, quality, flexibility and the opportunity costs. However, most economic evaluations of FMSs assume the problem is deterministic, such that they fail to model accurately and capture the nature of FMSs. This paper uses stochastic variables to capture the.nature of a FMS under given resource limitations and leads to a multistage chance-constraints linear programming (LP) formulation. Finally, in order to incorporate the uncertainty of capital investment, the interest rate as a function of time is considered over the whole planning horizon and the decision model is extended under continuous and variable discounting.     

The Usage of Opportunity Cost to Maximize Performance in Revenue Management*

To meet customer requirements efficiently, a manager needs to supply adequate quantities of products, capacity, or services at the right time with the right prices. Revenue management (RM) techniques can help firms use differential pricing strategies and capacity allocation tactics to maximize revenue. In this article, we propose a marginal revenue‐based capacity management (MRBCM) model to manage stochastic demand in order to create improved revenue opportunities. The new heuristic employs opportunity cost estimation logic that is unique and is the reason for the increased performance. The MRBCM model generates order acceptance policies that allocate available capacity to higher revenue generating market segments in both service and manufacturing environments. To evaluate these models, we design and conduct simulation experiments for 64 scenarios using a wide range of operating conditions. The experimental results show that the MRBCM model generates significantly higher revenues over the first come, first served rule when capacity is tight. In addition, we also show that the MRBCM model generally performs better than a recent RM model published in the literature.     

Analytical network process for software selection in product development: A case study

Application of software for manufacturing processes is one of the resolutions many enterprises have resorted to in the 21st century. This has been a result of increased complexity of products, globalization, rapid changes in technology and so on. The idea was that application of software especially for product development would increase the competitive advantage of industry nevertheless the irony has been that most of the investment in software has not achieved the expected results. We carry out a case study to introduce a methodology, the analytical network process as a multiattribute strategic decision making approach to help in the selection of appropriate software to suit the product development process of a particular product.     

Linking long-term capacity management for manufacturing and service operations

For firms that combine manufacturing and service operations in one system, the task of managing capacity is not straightforward. New goods and services may not have the same set of competitive priorities, and the models and concepts available in the literature for service operations differ from those for manufacturing operations. We address this problem and review the concepts and models for capacity management in the long term in both streams of literature, i.e. manufacturing and services, to develop a unified framework for manufacturing and service operations. The framework creates transparency between new goods manufacturing and service operations, since the same long-term capacity management structure is used for both product types, as well as between capacity strategy and planning strategy, since new goods and services are treated simultaneously. In the framework, the concepts of chase and level strategies are redefined for service operations to allow for integration with manufacturing operations. A case study demonstrates the usefulness of the integrated approach for long-term capacity management.     

A taxonomy of international manufacturing networks

Abstract

Manufacturing firms with multiple product groups do not need to involve all factories in the production of all product groups. Some factories may specialize on a small set of products, while others participate in the manufacturing of a broader set of products. However, current theories on international manufacturing networks do not explain in detail how organizations design international manufacturing networks for different products or product groups involving different sets of factories. This research investigates 20 product group networks at five global manufacturing firms. We distinguish between three types of factories: component manufacturing factories, assembly factories, and integrated factories (having both component manufacturing and assembly). Furthermore, we identify four network types: linear, divergent, convergent, and mixed structures. These four types exhibit distinctly different characteristics in terms of key characteristics, factory roles, product types, process types, market types, sourcing, and key managerial challenges. Most networks are relatively small – on an average consisting of four factories and some contain a number of subnetworks that are self-sufficient in terms of material flow and serve separate market regions. We identify two new types of factory roles related to component manufacturing competences, which we call ‘strategic feeder’ and ‘full lead’.     

Responsive Pricing Newsvendor Networks with Discretionary Commonality

Discretionary commonality is a form of operational flexibility used in multi‐product manufacturing environments. Consider a case where a firm produces and sells two products. Without discretionary commonality, each product is made through a unique combination of input and production capacity. With discretionary commonality, one of the inputs could be used for producing both products, and one of the production capacities could be used to process different inputs for producing one of the products. In the latter case, the manager can decide, upon the realization of uncertainty, not only the quantities for different products (outputs) but also the means of transforming inputs into outputs. The objective of this study is to understand how the firm's value, its inventory levels for inputs and capacity levels for resources are affected by the demand characteristics and market conditions. In pursuing this research, we extend Van Mieghem and Rudi ( 2002 )'s newsvendor network model to allow for the modeling of product interdependence, demand functions, random shocks, and firm's ex post pricing decision. Applying the general framework to the network with discretionary commonality, we discover that inventory and capacity management can be quite different compared to a network where commonality is non‐discretionary. Among other results, we find that as the degree of product substitution increases, the relative need for discretionary commonality increases; as the market correlation increases, while the firm's value may increase for complementary products, the discretionary common input decreases but the dedicated input increases. Numerical study shows that discretionary flexibility and responsive pricing are strategic substitutes.