Learning curve analysis in total productive maintenance

The continuous improvement concepts such as total quality management, just-in-time and total productive maintenance have been widely recognized as a strategic weapon and successfully implemented in many organizations. In this paper, we focus on the application of total productive maintenance (TPM). A random effect non-linear regression model called the Time Constant Model was used to formulate a prediction model for the learning rate in terms of company size, sales, ISO 9000 certification and TPM award year. A two-stage analysis was employed to estimate the parameters. Using the approach of this study, one can determine the appropriate time for checking the performance of implementing total productive maintenance. By comparing the expected overall equipment effectiveness (OEE), one can improve the maintenance policy and monitor the progress of OEE.     

What is the impact of sustainable development on the re-localisation of manufacturing enterprises?

Rendering the supply chain more eco-friendly is an innovative idea progressively adopted by industry. Our research focuses on the CO₂ equivalent emissions along the supply chain due to freight energy use and storage. A supply chain model based on discrete event simulation was developed. The model uses reorder point production management policy (ROP) within a make to stock (MTS) demand response strategy. Manufacturing capability is also taken into account using an overall equipment effectiveness indicator (OEE). In addition, the location of the firms and their types of products are modelled. The purpose is to compare supply chain CO₂ equivalent emissions of different configurations. This method is applied to two industrial cases: Carrier (UTC group), a large cooler manufacturer and Zannier group, a textile industry. The principle objective of the study is to conduct pertinent experiments to give green guidelines to Carrier and Zannier group.     

Strategic performance measurement in a healthcare organisation: A multiple criteria approach based on balanced scorecard

The Balanced Scorecard (BSC) methodology focuses on major critical issues of modern business organisations: the effective measurement of corporate performance and the evaluation of the successful implementation of corporate strategy. Despite the increased adoption of the BSC methodology by numerous business organisations during the last decade, limited case studies concern non-profit organisations (e.g. public sector, educational institutions, healthcare organisations, etc.). The main aim of this study is to present the development of a performance measurement system for public health care organisations, in the context of BSC methodology. The proposed approach considers the distinguished characteristics of the aforementioned sector (e.g. lack of competition, social character of organisations, etc.). The proposed measurement system contains the most important financial performance indicators, as well as non-financial performance indicators that are able to examine the quality of the provided services, the satisfaction of internal and external customers, the self-improvement system of the organisation and the ability of the organisation to adapt and change. These indicators play the role of Key Performance Indicators (KPIs), in the context of BSC methodology. The presented analysis is based on a MCDA approach, where the UTASTAR method is used in order to aggregate the marginal performance of KPIs. This approach is able to take into account the preferences of the management of the organisation regarding the achievement of the defined strategic objectives. The main results of the proposed approach refer to the evaluation of the overall scores for each one of the main dimensions of the BSC methodology (i.e. financial, customer, internal business process, and innovation-learning). These results are able to help the organisation to evaluate and revise its strategy, and generally to adopt modern management approaches in every day practise.     

The relationship of subjective distress and emergency response experience to the effective use of protective equipment

A total of 11 1 chernical emergency response team members were evaluated on the effective use ofpersonal protective equipment (PPE) and self-contained breathing apparatus (SCBA) whde participating in a series of simulated hazardous material accidents. Performance ratings of PPE and SCBA use were conducted via behaviourally anchored rating scales (BARS), self-estimates of effectiveness, and cohort ratings. Subjective distress was assessed via the Subjective State Change Measure (SSCM), State-Trait Anxiety Inventory, and the Framingham Type A Behaviour Scale. Results indicated that effective use ofprotective breathing apparatus was correlated with prior emergency response experience and state anxiety. BARS scores were negatively related to state anxiety when controlling for experience. Self-ratings for effectiveness was positively related to both type A behaviour pattern and state anxiety.     

Rejects reduction in a retail bank using Lean Six Sigma

Lean Six Sigma (LSS) is a majestic process improvement methodology that has been proved to be a powerful management strategy across services. The influential synergy of Six Sigma and Lean aims at improving the processes, focusing on both rapid and robust improvements, reducing waste and variation in the process. LSS generates successful results in key performance indicators (KPIs) based environments, where process data gets measured and leveraged for making essential management decisions. The aim of this paper is to highlight the importance of LSS in banking industry through a real-time process improvement study. The article establishes the literature for the need for LSS in banks detailing on customer facing metrics and process KPIs. An action-research study conducted in a retail bank is presented in LSS DMAIC methodology which reaped a benefit of INR 1.6 million and is a classic example of how LSS can bring bottom-line impact to an organisation, alongside contributing to the process improvement mind-set in employees.     

Methods for Managing Different Perspectives of Project Success

The results of an exploratory study of UK organizations into methods for meeting project key performance indicators (KPIs) are presented. The paper explores: influences on the use of methods to manage project KPIs; the need for and existence of methods; the factors that facilitate the meeting of the KPIs. It is concluded that the use of methods varies depending upon the perceived importance of the project, the type of project, the client-team relationship and whether an organization performance management system exists. With project management capability often decreasing, in part due to a failure to meet psychosocial project KPIs, a need for methods linked to the KPIs was identified. However, the study found relatively low levels of adoption of such methods. Where psychosocial project KPIs were being met the following facilitating factors emerged: top-level policies, organization-wide training, integration with existing management processes, building into project management system. Situations were found where decision-makers did not consider the psychosocial KPIs of programme and project managers. This was seen to contribute to a failure by organizations to manage necessary increases in their project management capability and to be acting as a possible barrier to long-term, sustainable improvements in performance.     

A decision support system for the selection of a casting process using analytic hierarchy process

This paper presents an Analytic Hierarchy Process (AHP) based decision support system to select the most suitable casting process for a given product. The hierarchical structure of the proposed method allows the decision maker to compare the different casting processes using the material suitability and flexibility, geometrical complexity, dimensional tolerance and surface finish of the casting, and the cost as the criteria for selection. Judgemental inconsistency of the decision maker in selecting the casting process is taken care by ensuring that the value of consistency ratio is below (0.1). A numerical example is presented to illustrate the effectiveness of the proposed methodology for selecting the suitable casting process.     

Improving throughput for an electronic assembly line using a constraint analysis methodology

Electronic assembly operations are vital to industries such as telecommunications, computers and consumer electronics. This paper presents a constraint analysis methodology for planning and improving electronic assembly operations that draws on concepts from queueing theory, simulation and production planning. The proposed methodology identifies the operational bottleneck and predicts the utilization, throughput and lead time of the assembly line. It also quantifies the relationship between yields and utilization for the assembly operations. A case study is presented that applies the methodology at an Ericsson, Inc., telecommunications equipment assembly facility. The constraint analysis methodology provided valuable decision support as the managers of Ericsson evaluated the costs and benefits of additional production capacity. Although the focus of this paper is electronic assembly operations, the methodology can be applied to general flow line assembly systems with feedback loops for test and rework under dedicated high-volume production.     

Production planning for remanufactured products

This paper presents a methodology for production planning within facilities involved in the remanufacture of products. Remanufacturing refers to the process of accepting inoperable units, salvaging good and repairable components from those units, and then re-assembling good units to be re-issued into service. These types of facilities are common, yet many suffer from the unpredictability of good and repairable component yields, as well as processing time variation. These problems combine to make it extremely difficult to predict whether overall production output will be sufficient to meet demand. Low yields of key components can lead to shortages which require the facility to purchase new components for legacy systems, often with long lead times, thus causing overall delays. The approach developed here is a probabilistic form of standard material requirements planning (MRP), which considers variable yield rates of good, bad, and repairable components that are harvested from incoming units, and probabilistic processing times and yields at each stage of the remanufacturing process. The approach provides estimates of the expected number of remanufactured units to be completed in each future period. In addition, we propose a procedure for generating a component purchase schedule to avoid shortages in periods with a low probability of meeting demand. The proposed methodology is applied to an antenna remanufacturing process at the Naval Surface Warfare Center (NSWC). In this case study the proposed methodology identifies a potential shortage of a key component and suggests a corrective action to avoid significant delay in the delivery of remanufactured units.     

Enabling the seamless supply chain by exploiting the four smooth material flow controls

A decade after the publication of the concept of smooth material flow via four fundamental principles related to the work of Jay Forrester and John Burbidge (FORRIDGE) the influence of this work on academe and industry is discussed. We show that by extension of their principles via a three-level model which includes the vision and the toolkit, substantial contributions have been made towards new management theory. The associated 12 simplicity rules and uncertainly circle concepts have been exploited within the structured framework provided by the quick scan audit methodology. This generates value stream classification ranging from baseline to exemplar, and a design procedure aimed at material flow best practice. A detailed case study demonstrates the improved industrial performance achievable by this means.     

The introduction of Kanban principles to material management in EWSD production

Kanban systems combine two distinct and important functions. They control the flow of material through the manufacturing plant and they act as identifiers for deficiencies in the logistics of the production chain. This paper describes a Kanban system recently introduced to a Siemens manufacturing plant for telecommunication switching equipment in Florida, USA. Almost all stages of the formerly push-based manufacturing process were linked to each other through various types of pull systems. Ultimately, the system was extended to include suppliers of material. Emphasis is given to the importance of the planning and implementation processes since they have proven to be crucial to the success of the system.     

Action e-learning: An exploratory case study of action learning applied online

Abstract

Web-based instruction, also called e-learning, is currently one of the most talked-about education and training media. To prepare courses for online delivery and to maintain their effectiveness, the designer must have an understanding of e-learning instructional design principles. Action learning is a proven, effective management development process that has not been implemented to date as an e-learning instructional methodology. The purpose of this exploratory case study was to examine the impact of the action learning process on the effectiveness of management level web-based instruction (WBI). A leader-led, management-level course using face-to-face delivery was converted to web-based instruction where action learning was the delivery methodology. Kirkpatrick's Four Levels of Evaluation served as the evaluation tool to determine effectiveness of the intervention. It was found that, though challenging to facilitate, the action learning online method is effective and yields changes in participants' knowledge. However, contrary to expectations, online learning communities did not form.     

Multi-output profit efficiency and directional distance functions

We extend a recently developed DEA methodology for cost efficiency analysis towards profit efficiency settings. This establishes a novel DEA toolkit for profit efficiency assessments in situations with multiple inputs and multiple outputs. A distinguishing feature of our methodology is that it assumes output-specific production technologies. In addition, the methodology accounts for the use of joint inputs, and explicitly includes information on the allocation of inputs to individual outputs. We also establish a dual relationship between our multi-output profit inefficiency measure and a technical inefficiency measure that takes the form of a multi-output directional distance function. Finally, we demonstrate the empirical usefulness of our methodology by an empirical application to a large service company.     

Six things to manage--Designs

Transportation in reverse logistics (RL) plays a significant role and has impact on overall RL performance. Efficiency, effectiveness and impact are the distinct components of RL transportation. Balancing these components requires the implementation of an effective performance measurement (PM) system. The perspectives of balanced scorecard have been used where enterprises can link their performance to their transportation practices, which do not provide an understanding of the RL transportation operating objectives and the developing strategies through an analysis of stakeholders. This article proposes the comprehensive PM of transportation system, which is multi-angle perspective for RL enterprises. Recognising the multiple criteria nature of the problem, this article uses analytical hierarchy process methodology in order to find an overall comprehensive performance index, which is critical to the success of the RL transportation operations to assist logistics managers, researchers, transportation planners and decision-makers.     

Engineering change: A theoretical assessment and a case study

The competitive playground where nowadays firms struggle to survive has rapidly become unforeseeable: product life cycle has shrunk, becoming even shorter than in the past, and world-wide market is suffering for a strong customer differentiation which led to an increasingly wide product mix. In this industrial environment, the engineering change process is getting more and more attention throughout the branches of industry, as it appears as a critical process which seeps into the operations management core, thus influencing the overall firm's performances. A brief state-of-the-art in the area of engineering change is firstly presented. Then a proposal of classification and a new methodology for an effective engineering change process management are suggested. The new proposed methodology has been successfully applied to a real-life manufacturing system and the related case study is reported at the end of the paper.     

A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing

This paper investigates an integrated production and transportation scheduling problem in an MTO supply chain. A harmony search-based memetic optimization model is developed to handle this problem, in which certain heuristic procedures are proposed to convert the investigated problem into an order assignment problem. A novel improvisation process is also proposed to improve the optimum-seeking performance. The effectiveness of the proposed model is validated by numerical experiments. The experimental results show that (1) the proposed model can solve the investigated problem effectively and that (2) the proposed memetic optimization process exhibits better optimum-seeking performance than genetic algorithm-based and traditional memetic optimization processes.     

Fuzzy Overall Equipment Effectiveness (FOEE): capturing performance fluctuations through LR Fuzzy numbers

The paper focuses on the Overall Equipment Effectiveness (OEE), a performance indicator that is extensively used in the industry. The aim is to extend the capabilities of the OEE, so as to capture the day-to-day fluctuations to which manufacturing performances are subjected. To this aim, manufacturing losses are decomposed into elementary causes and modelled as LR fuzzy numbers. Next, in order to compute the Fuzzy Overall Equipment Effectiveness (FOEE), single losses are aggregated using the ‘fuzzy transformation model’. This approach limits the fuzzy overestimation phenomenon and assures both results’ accuracy and robustness. An industrial application, part of a lean project carried on by an important Italian manufacturing firm, is finally presented. Results are encouraging, since the FOEE made it possible to trace back the share of the overall fluctuations that is ascribable to each cause of loss. In this way, it provided the basis for setting improvement priorities and directed the lean team toward the selection of appropriate corrective actions.     

An intelligent workstation controller for integrated planning and scheduling of FMS cell

This paper presents an experimental design developed to determine a combination of robust planning and scheduling rules for an intelligent workstation controller (IWC). The IWC is used as part of the control system for an automated flexible manufacturing system. A three-level hierarchical control structure (shop, workstation and equipment)is adopted in order effectively to control a shop-floor. At the top level is a shop controller which receives orders and their associated manufacturing information, and manages interactions among workstations. The IWC defines and resolves the production control activities necessary to coordinate a group of equipment controllers so as to ensure the completion of orders. Specifically, the IWC is responsible for selecting a specific process routeing for each part, allocating resources, scheduling and coordinating the activities across the equipment, monitoring the progress of activities, detecting and recovering from errors, and preparing reports. These activities are accomplished using planning, scheduling, and execution functions. In order to demonstrate the effectiveness and robustness of the IWC, all the controllable and uncontrollable factors need to be identified and detailed. Controllable factors are those which are set by the controller and cannot be directly affected by the production environment. Uncontrollable factors are those which vary with the production environment and cannot be directly changed by the controller developer. The objective of the paper is to illustrate how a good set of controllable factors that dictate the IWC's effectiveness and robustness over various uncontrollable factors can be determined. Due to the number of possible combinations of all the factors, a complete validation of the effectiveness and robustness of the IWC is extremely time consuming and far beyond the scope of this paper. Therefore, a few planning and scheduling strategies are selected and a formal experiment is conducted. The experiment illustrates how significant performance dependencies for various planning and scheduling strategies can be identified.     

多级供应链系统成本分析随机网络模型及算法研究

供应链成本管理是企业战略管理的核心组成部分。为研究多级供应链网络系统的成本组成及其分布特征、分析各节点企业的成本管理对多级供应链网络系统的影响、找到供应链系统成本管理中的薄弱环节和关键企业,本文构建了多级供应链系统成本的随机网络分析模型。首先研究了模型的结构性质特征,给出成本分布特征的解析算法。然后扩展模型,分别从系统成本类型构成(生产成本、库存成本和物流成本)和系统对企业成本波动的灵敏度两个角度深入研究多级供应链网络成本问题。数值算例分析结果说明了多级供应链网络系统成本分析模型和相关算法的有效性和实用性。     

Redesigning a Cellular Manufacturing System to Handle Long-Term Demand Changes: A Methodology and Investigation*

Cellular manufacturing systems have been proposed as an alternative to the job shop since they provide some of the operational benefits of a flow line production process, while retaining to some extent the flexibility of job shops. However, this must be balanced against the possibility of additional initial investments in equipment to form the cells and a certain loss in manufacturing flexibility, particularly in terms of the ability to deal with long-term demand changes. This paper presents a model-based heuristic cell system redesign methodology to deal with such demand changes. The methodology is validated and applied to system designs generated from several data sets published in the literature. Results show that different kinds of demand changes incur distinct kinds of costs. Further, characteristics of cell designs that can handle long-term demand changes at least cost are identified.