Defining and Dimensionalising Diversity:: Evidence from Corporate Websites across Europe

The corporate ‘diversity statement’ is a new tool increasingly used by large companies to promote diversity management policies on their websites. Through an examination of these on-line texts, we identify how companies construct the meaning of ‘diversity’ through its dimensions. Few companies actually define diversity. However, dimensions of diversity cover a wide-ranging set of individual differences, not just gender and race but other visible and less visible differences that might lead to discrimination in the workplace. By comparing statements from 241 top companies in eight countries (Finland, France, Germany, Netherlands, Norway, Sweden, Switzerland and the UK), we reveal how the definition of ‘diversity’ and its dimensions as used on websites varies across Europe.     

Development and analysis of mathematical and simulation models of decision-making tools for remanufacturing

This article presents decision-making tools for remanufacturing. The first decision-making tool was used to address inventory lot-sizing problems in a hybrid remanufacturing–manufacturing system with varying remanufacturing fraction. In this article, the new inventory lot-sizing model with variable remanufacturing lot sizes has been shown to exhibit better performance than the benchmark model with fixed remanufacturing lot sizes. The new inventory lot-sizing model is anticipated to become a valuable decision-making tool in companies that are planning to adopt remanufacturing. The second decision-making tool was applied to address a production and inventory planning problem in a remanufacturing system considering different remanufacturing policies for a given remanufacturing strategy. For a remanufacture-to-stock system with two quality remanufacturables groups four alternative policies were examined, a policy which specifies simultaneous processing utilising dedicated resources was shown to be the best policy to achieve a shorter remanufacturing cycle time. For a remanufacture-to-order system with two quality remanufacturables groups, the three relevant policies of the four alternative policies were examined, a policy which specifies sequential processing and switching between various quality remanufacturables groups was shown to be the best policy to achieve a shorter remanufacturing cycle time. The production and inventory planning simulation models in a remanufacturing system are expected to become significant decision-making tools in remanufacturing operations.     

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.     

回收物流库存控制研究

本文探讨了包含回收品的库存系统。回收物流库存中既有一般生产过程的新产品,也有经再制造的回收品,使其最优库存策略非常复杂,论文推导出不同控制方式下的EOQ模型,以确定最优生产和再制造批量。此外,还对求得的最优批量进行适当的调整,以确保在循环周期中的定货次数为整数。该模型形式、结构简单易于在实践中应用。     

考虑故障停机的生产控制与维修计划联合决策模型

通过生产控制与维修计划协同决策,降低生产成本。首先描述生产过程,分析各项费用。其次,建立了考虑生产过程失控、故障率和故障停时间的生产过程控制、生产计划优化和维修管理联合优化决策的模型。通过模型求解,联合制定出生产过程检查策略、生产计划（经济生产批量、生产批次）以及维修计划（PM间隔期）,实现单位时间内总费用最低的目标。再次,案例研究,分析生产过程失控、故障率和故障停机时间对于经济生产批量、生产过程检查策略和生产系统维修计划的影响。该模型从理论上解决了生产过程控制、生产计划优化和维修管理联合优化决策难题,对于指导企业制定生产计划和生产系统的检修计划,进而提高产品质量、降低生产成本、确保准时交货都具有指导意义和实用价值。     

Effects of maintenance policies on the productivity of flexible manufacturing cells

Flexible manufacturing cells (FMCs) often operate with increasing failure rate due to extensive utilization and wear-outs of equipment. While maintenance plans can eliminate wear-out failures, random failures are still unavoidable. This paper discusses a procedure that combines simulation and analytical models to analyze the effects of corrective, preventive, and opportunistic maintenance policies on productivity of a flexible manufacturing cell. The production output rate of an FMC, which is a function of availability, is determined under different maintenance policies and mean time between failures.     

The disassembly line: balancing and modeling,by S.M. McGovern and S.M. Gupta

This note addresses a problem faced by an actual firm. The problem is to decide on the optimal level of product quality. In performing the economic analysis to determine product quality level, the firm considers revenue, production costs, and research and development costs. However, this note shows that ignoring inventory costs in the analysis will lead to suboptimal product quality levels. Also, including inventory costs in the analysis will lead to reduced production lot sizes. Numerical examples are used to illustrate the results of the model.     

Components supplier patterns in the UK motor industry

There has been tremendous Western interest in the ‘Japanese’ model of manufacturing, particularly in the motor industry in recent years. Western vehicle assemblers profess to be developing closer, higher trust relations with their suppliers to support practices such as just-in-time production and total quality. Comparatively little work has been carried out into the relations between first tier suppliers and their suppliers. This paper reports a study into the relations between a UK ‘first tier’ supplier to the European vehicle industry and 29 of its suppliers, and describes how the Japanese manufacturing model is making itself felt beyond the first tier suppliers.     

A production model for deteriorating items with stochastic preventive maintenance time and rework process with FIFO rule

Due to unreliable production facility and stochastic preventive maintenance, deriving an optimal production inventory decision in practice is very complicated. In this paper, we develop a production model for deteriorating items with stochastic preventive maintenance time and rework using the first in first out (FIFO) rule. From our literature search, no study has been done on the above problem. The problem is solved using a simple search procedure; this makes it more practical for use by industries. Two case examples using uniform and exponential distribution preventive maintenance time are applied. Examples and sensitivity analysis are conducted for each case. The results show that rework and preventive maintenance time have significant affected the total cost and the optimal production time. This provides helpful managerial insights to help management in making smart decisions.     

The effects of learning and forgetting on the optimal lot size quantity of intermittent production runs

This paper studies the effects of learning and forgetting on the production lot size problem with infinite and finite planning horizons. It is assumed that the determination of the economic manufactured quantity (EMQ) in the succeeding production run is dependent on: (1) the maximum inventory accumulated prior to interruption; (2) the length of the interruption period which incurs total forgetting; and (3) the level of experience in equivalent units remembered at the start-up of the next production run. The optimum operating inventory doctrines is obtained by trading off procurement cost per unit time and the inventory carrying cost per unit time, so that their sum will be a minimum. A numerical example is presented to demonstrate the application of learning and forgetting to the determination of the EMQ.     

A production model for deteriorating items with stochastic preventive maintenance time and rework process with FIFO rule

Due to unreliable production facility and stochastic preventive maintenance, deriving an optimal production inventory decision in practice is very complicated. In this paper, we develop a production model for deteriorating items with stochastic preventive maintenance time and rework using the first in first out (FIFO) rule. From our literature search, no study has been done on the above problem. The problem is solved using a simple search procedure; this makes it more practical for use by industries. Two case examples using uniform and exponential distribution preventive maintenance time are applied. Examples and sensitivity analysis are conducted for each case. The results show that rework and preventive maintenance time have significant affected the total cost and the optimal production time. This provides helpful managerial insights to help management in making smart decisions.     

Single-Stage and Serial Production Line Systems with Unreliable Machines and General Probability Distributions

This paper presents stochastic models for analyzing production to stock and production on demand systems with arbitrary demand, production, machine breakdown and repair processes, and a finite buffer. Expressions are developed for the transition probabilities among the different states, the proportion of transitions that take the process to a particular state, the probabilities that the process is at a particular state, and the expected state residence times. Also, expressions are developed for some quantities of interest, like average inventory, percentage of lost sales, and expected waiting time. Applications are discussed for various demand, production, machine breakdown, and repair processes and numerical examples are presented. Guidelines are given for utilizing the models in evaluating the economic performance of production systems. Using an approximation procedure, the models are used for modeling multi-stage serial production to stock and production on demand lines. Simulation results indicated that the quality of the approximation is very good. The multi-stage models are useful in practical situations, because they allow the use of different probability distributions for the various processes (production, machine failure, etc.) of each stage.     

Optimal production,replenishment, delivery,routing and inventory management policies for products with perishable inventory

This paper presents a generalized production-inventory-routing model with perishable inventory. We analyze the optimal integrated decisions of when and how much to deliver and sell products with varying manufacturing periods. We discuss main inventory management policies to demonstrate the applicability of the model in real-world applications for production routing problems (PRPs) with perishable inventory. Furthermore, an exact branch-and-cut algorithm is developed and discussed. We introduce new families of logical, strengthened lot-sizing and lifted Miller–Tucker–Zemlin subtour elimination constraints for the PRP with perishable inventory. Finally, we test the performance of the algorithm. We also implement and compare 8 suboptimal delivery and selling priority policies with an optimized policy to develop managerial implications.     

Systems thinking and business process redesign: An application to the beer game

Managers are regrettably ignorant of the fact that their business organisations are ‘designable’. But recently, concepts such as business re-engineering and systems thinking, coupled with advances in methods of quantifying business systems, have enabled managers to scrutinise their business systems afresh.Ann van Ackere, Erik Reimer Larsen and John Morecroft use a well-known logistical system — the ‘beer game’ — to illustrate these re-engineering concepts and tools in a multi-stage production and distribution system involving a single brand of beer. This business game raises the fundamental question of why it is so difficult to match shipments and factory production to consumer demand.The authors conclude that such re-design concepts and tools can be applied successfully to full-scale business problems. Systems thinking, modelling and continuous time simulation can provide the framework for carrying the design process from mapping all the way through to redesign. The most effective CEOs of the future will be those who are competent to create corporate design in which employees are allowed to succeed.     

Lessons from the ‘made in Switzerland’ study: What makes a world-class manufacturer?

Many executives are currently striving to develop world-class manufacturing operations to ensure that they remain competitive in increasingly global markets. To do this, they are adopting a range of practices, from organisational changes such as empowerment and teamwork to the use of techniques such as pull production. Their goal is to substantially improve performance: faster cycle times, reduced manufacturing costs and greater customer satisfaction.The question of how far companies have moved towards world-class manufacturing is at the heart of the ‘Made in Switzerland’ project, a major benchmarking study of Swiss manufacturing practice and performance. The study was carried out in 1995 by IMD faculty and researchers working with consultants from IBM Switzerland. It is part of the internationally-based ‘Made in Europe’ project comprising similar studies in the UK, Germany, The Netherlands and Finland.The central hypothesis of the studies is that the adoption of best practice leads to high performance. The objective is to establish a benchmarking database for participating manufacturers around the world. The studies, which are highly structured, examine six areas of manufacturing practice and performance in detail and assess the relationship between them at individual plants. The areas covered in the study are quality, organisation and culture, concurrent engineering, logistics, lean production and manufacturing systems.Plants in each country are grouped according to their position on the practice and performance indices and then studied in order to pinpoint the issues and challenges facing the manufacturers within that group. Less than three per cent of the 800 plants currently on the ‘Made in Europe’ database are considered ‘world-class’. Yet for manufacturers striving to reach this level of performance, this small minority can provide some valuable insights for the way ahead.This article discusses many of the issues raised by the analysis described above, with particular reference to the ‘Made in Switzerland’ study. In the first section, it looks at the key lessons arising from the Swiss study and what insights these can provide for manufacturers, not only in the Swiss market, but across Europe. In the second section, it looks at how the study can be used for benchmarking and provides manufacturers with some general recommendations to help them focus their improvements and move closer to becoming world-class.     

Reassessing Tradeoffs Inherent to Simultaneous Maintenance and Production Planning

Previous work has considered the simultaneous (as opposed to sequential) optimization of a maintenance policy and a production policy in a multi‐product setting with random yield and product mix constraints. One of the sequential approaches to which the simultaneous approach is compared is a so‐called first‐come‐first‐served (FCFS) approach, i.e., an approach that generates randomized production policies that do not depend on the deterioration state of the machine. However, the model formulation for this approach does not generate policies consistent with this FCFS notion. Therefore, we present a revised FCFS model and analyze its performance using an existing experimental design. The results suggest that previous work overestimates the degree to which a FCFS approach is suboptimal, and underestimates the value of simultaneously optimizing the maintenance and production decisions. Lastly, we conduct additional experiments which suggest that the joint impact of using both simultaneous optimization and a deterioration dependent production policy is quite significant.     

Optimal maintenance intervals for a multi-component system

In the manufacturing industry, preventive maintenance (PM) is carried out to minimise the probability of plant unexpected breakdown. Planned PM is preferred as disruption to operation is then minimised. Suggested PM intervals are normally prepared by the original equipment manufacturers (OEMs), however due to the multifaceted relationship between operating context and production requirement for different plants, it is unlikely that these suggested intervals as prescribed by the OEMs are optimal. Reliability, budget and breakdown outages cost are some of the critical factors that will affect the calculation of optimal maintenance intervals. Maintenance managers are required to determine optimal maintenance intervals with the above different requirements set by management. In this paper three models are proposed to calculate optimal maintenance intervals for multi-component system in a factory subjected to minimum required reliability, maximum allowable budget and minimum total cost. Numerical examples are provided to illustrate the application and usefulness of the proposed models.     

The impact of random machine unavailability on inventory policies in a continuous improvement environment

There are production situations where a production facility (e.g. a machine) is used intermittently to produce lot sizes of certain products. Upon completion of production run, the facility may not be available for a random amount of time due to several reasons, such as: the facility needs to be maintained and the maintenance time is random due to unforeseen circumstances; or that the facility is leased by different manufacturers and the demand for the facility is random. As a result of machine unavailability, stock-out situations might arise. This paper extends the work of Abboud et al . (2000, Computers and Operations Research , 27 , 335-351) by assuming learning and forgetting in production. A new mathematical model is developed with numerical examples and sensitivity analysis provided. Furthermore, this paper determines how the overall inventory cost is influenced by the nature of the random variable that represents the unavailability time of the production facility.     

Integrated procurement- production system in a just-in-time environment-modelling and analysis

Classically, economic lot size models have been used separately for procurement and production subsystems. However, when the raw materials are used in production, the procurement policies are dependent on the schedule and the batch size for the product. Hence, it is necessary to unify the procurement and production policies. The just-in-time JIT environment provides an ideal setting for such a coordination between the procurement and production policies. The model proposed here is a traditional inventory model recast into a model for a JIT system for a single product, multistage batch environment aiming at the minimization of total variable cost and thereby determining the batch sizes for the product and raw material order sizes. A JIT system aims at minimizing setup time and this feature is captured in the proposed model. The computational experience reported in this paper is based on a number of simulated problem sets. The possible domain of application is also highlighted.     

Integrating strategic issues into strategic management

The notion of a ‘strategic issues’ is rather pervasive in the field of planning in both conceptual [5, 19] and practical contexts. For instance, sometime ago the Wall Street Journal [41] reported that at least 50 large firms have created positions of ‘issues management director’; a dramatic increase in the number of such positions. ‘True’ strategic issues have a readily apparent importance to any organization; yet the process of identifying such issues and of integrating them into strategic planning and management is not well developed. Most treatments of strategic issues deal only with specific segments of the overall process through which relevant issues may be initially identified and finally translated into appropriate strategy [e.g. 5, 17]. This paper demonstrates that it is practical to develop a comprehensive process of ‘strategic issue management’ (SIM) that will facilitate the systematic identification, assessment and analysis of such issues. Such a process can ensure that issue-related factors are fully integrated into the formulation and implementation of strategy and plans. As such, SIM is a process whereby strategic issues may become an integral element of strategic management.