Improving overall equipment cost loss adding cost of quality

This research has the objective of improving indicators for evaluating losses of equipment. It also proposes a newly developed computing methodology for estimating the quantitative losses in monetary unit. The presented methodology is to calculate losses following overall equipment effectiveness (OEE) consisting of opportunity and production cost losses and also from cost of quality (COQ) approaches. This method eliminates some of OEE's weaknesses and expands scope from overall equipment cost loss (OECL). The proposed calculating methodology is demonstrated by applying to a real manufacturer of equipment. This newly improved model can prioritise problematic equipment more appropriately than OEE and OECL.     

Performance measurement using overall equipment effectiveness (OEE): literature review and practical application discussion

The quest for improving productivity in the current global competitive environment has led to a need for rigorously defined performance-measurement systems for manufacturing processes. In this paper, overall equipment effectiveness (OEE) is described as one such performance-measurement tool that measures different types of production losses and indicates areas of process improvement. Analysis is done on how OEE has evolved leading to other tools like total equipment effectiveness performance, production equipment effectiveness, overall factory effectiveness, overall plant effectiveness, and overall asset effectiveness. Two industrial examples of OEE application are discussed, and the differences between theory and practice analysed. Finally, a framework for classifying and measuring production losses for overall production effectiveness is proposed. The framework harmonizes the differences between theory and practice and makes possible the presentation of overall production/asset effectiveness that can be customized with the manufacturers needs to improve productivity.     

Optimal joint maintenance and operation policies to maximise overall systems effectiveness

In this paper, the problem of determining the optimal maintenance and operation policies for a multi-state, multi-stage machine maintenance problem is considered. This problem has been formulated in the literature as a Partially Observed Markov Decision Process (POMDP). A new formulation that explicitly ties maintenance, operation, and quality within the POMDP framework is provided. The new formulation maximises Overall Systems Effectiveness for an n-state system with multiple speed and maintenance actions. The model provides, for each time epoch, a set of optimal maintenance and production-rate actions. The decision-maker (controller) can select the optimal policy depending on the system state occupancy vector (belief state). A realistic numerical model is presented to demonstrate the model utility.     

Optimizing OEE,productivity and production cost for improving sales volume in an automobile industry through TPM: a case study

The aim of this paper is to investigate how increase in sales volume has evolved by improving overall equipment effectiveness (OEE) of machines, plant productivity and production cost through total productive maintenance (TPM) initiatives in a reputed tractors manufacturing industry in India. In the present scenario of global competitive market, the manufacturing industry needs to improve their operational performance for surviving and prospering. TPM is practised by industry as a business tool for rapid and continuous improvement in its manufacturing capabilities. OEE offers a powerful control tool to overcome production deficiencies and operational performance constrains. Productivity and manufacturing cost are also crucial operational measures to analyse the manufacturing performance. In this study, evaluation and analysis of the methodology adopted for improving sales volume through TPM initiatives was carried out using an interactive research approach. The industrial example on the application of OEE tool demonstrates that it has a remarkable potential to enhance the equipment effectiveness. The empirical findings of the study reveal that augmented OEE and productivity, and reduced production cost resulted to double the sales revenue and triple the profit within a period of three years. The industry also achieved notably tangible and intangible benefits with the TPM implementation.     

Process improvement in healthcare: overall resource efficiency

This paper aims to develop a unifying and quantitative conceptual framework for healthcare processes from the viewpoint of process improvement. The work adapts standard models from operation management to the specifics of healthcare processes. We propose concepts for organizational modeling of healthcare processes, breaking down work into micro processes, tasks, and resources. In addition, we propose an axiological model which breaks down general performance goals into process metrics. The connexion between both types of models is made explicit as a system of metrics for process flow and resource efficiency. The conceptual models offer exemplars for practical support in process improvement efforts, suggesting to project leaders how to make a diagrammatic representation of a process, which data to gather, and how to analyze and diagnose a process's flow and resource utilization. The proposed methodology links on to process improvement methodologies such as business process reengineering, six sigma, lean thinking, theory of constraints, and total quality management. In these approaches, opportunities for process improvement are identified from a diagnosis of the process under study. By providing conceptual models and practical templates for process diagnosis, the framework relates many disconnected strands of research and application in process improvement in healthcare to the unifying pursuit of process improvement. Copyright © 2011 John Wiley & Sons, Ltd.     

Advanced bio-inspired structural materials: Local properties determine overall performance

Natural materials have always attracted intensive attention from multidisciplinary scientists all over the world. In fact, the ingenious and reasonable synthetic strategies of the limited components can always make natural materials achieve a superior performance that is far beyond their own. Meanwhile, the local properties can determine the overall performance through regulating multiple characteristics, including structure, composition, and interface. Living organisms can inspire the fabrication of artificial materials, which provides a clear vision for advanced materials research. Therefore, inspired by this strategy, biomimetic structural materials are used to meet the strict and even extreme requirements of engineering materials. In this review, we mainly clarify the difference of local properties in natural materials and explain how living organisms utilize very limited elements and compounds to control the local properties and further realize some specific function to adapt to the specific requirement of the environment. In addition, the manufacturing technologies and strategies common to bio-inspired structural materials are summarized. Finally, a summary and prospects on the limitations of current techniques and the direction of future developments for the design of novel bio-inspired materials are given.     

全热交换器交换效率影响因素的试验研究

试验研究全热交换器的交换效率的影响因素。试验表明,全热交换器的风量、风压的变化对全热交换器的交换效率有较大的影响。     

Modelling maintenance effects on manufacturing equipment performance: results from simulation analysis

Equipment maintenance and system reliability are important factors affecting the organisation’s ability to provide quality and timely services to customer. While maintenance remains an important function to manufacturing, it is only recently that attempts have been made to quantify its impact on equipment performance. In this research, an approach of linking maintenance with equipment performance is developed using simulation modelling. The modelling approach involves defining probabilistic models and assumptions affecting system performance, such as: the probabilistic model for the initial failure rate/intensity of the equipment; the probabilistic model for the system deterioration and corresponding effect; the probabilistic model for the random times of corrective maintenance (CM) and preventive maintenance (PM) that takes into the account the types of maintenance plans/policies and the potential dependency between CM and PM times; and the probabilistic model for the random effects of CM and PM on the reliability of the equipment. Using a continuous manufacturing equipment, the model is used to analyse the impact of deterioration, failures and maintenance (policies, timing and efficiency) on equipment performance. It is shown that modelling the effect maintenance provides a basis of evaluating maintenance efforts with the potential application in performance evaluation and decision support while investigating opportunities for manufacturing equipment performance improvement.     

OEE多维数据分析系统的应用研究

针对生产领域中重要效率评价指标OEE,研究如何用多维的思路和方法来分析.结合OEE的定义、多维分析基本思想,以及当前各类OEE分析软件特点的基础,为实现对海量多维生产数据准确、高效、灵活的分析,提出一种OEE多维数据分析系统.讨论了多维数据分析技术在OEE数据分析系统的研究和应用的设计过程,并对基于Excel VBA开发的OEE多维数据分析系统进行实证研究.     

Criteria for a lean organisation: development of a lean assessment tool

Lean principles have long been recognised as a competitive advantage. Although there are several measures for various aspects of lean production in the literature, there is no comprehensive measure for overall lean implementation in business firms. An appropriate measurement tool is needed to assess the effectiveness and efficiency of the lean implementation throughout the entire organisation. Based on lean research, a comprehensive tool called the leanness assessment tool (LAT) is developed, using both quantitative (directly measurable and objective) and qualitative (perceptions of individuals) approaches to assess lean implementation. The LAT measures leanness using eight quantitative performance dimensions: time effectiveness, quality, process, cost, human resources, delivery, customer and inventory. The LAT also uses five qualitative performance dimensions: quality, process, customer, human resources and delivery, with 51 evaluation items. The fuzzy method allows managers to identify improvement needs in lean implementation, and the use of radar charts allows an immediate, comprehensive view of strong areas and those needing improvement. Practical uses of the LAT are discussed in the conclusion, along with possible limitations.     

AI设备综合效率分析与提升

设备综合效率（OEE）是评价当前设备的运行时间、运行速度、良品率、维修成本的一个综合指标,也是衡量生产活动中由设备创造的附加价值的尺度。对某电子产品生产企业AI设备综合效率进行了计算与分析,找出了导致其OEE低下的主要原因,并设计了AI设备综合效率提升方案,该设计方案的应用实施,使AI车间OEE水平达到目标水平,为稳定、高效的生产提供了支持和保障。     

The moderating role of temporary work on the performance of lean manufacturing systems

Companies are extensively employing lean manufacturing practices and temporary work, which at face value are in stark contrast to each other. While lean manufacturing emphasises the value of workers, temporary work refers to precarious work arrangements that, based on social exchange theory, may harm workers’ commitment. The objective of this paper is to unveil the role of temporary work on the lean manufacturing – operational performance (i.e. cost, quality, delivery, flexibility) relationship. To answer our research question and test our hypotheses we utilise cross-country data collected through the sixth iteration of the International Manufacturing Strategy Survey and conduct multilevel regression analysis. Our results indicate that while lean manufacturing improves operational performance, the use of temporary work positively influences the relationship between lean manufacturing and mix and volume flexibility performance.     

A framework for assessing the use of lean production practices in manufacturing cells

This study introduces a framework for assessing the use of lean production (LP) practices in manufacturing cells (MCs). The development of the framework included four stages: (a) defining LP practices applicable to MC, based on criteria such as the inclusion of practices that workers could observe, interact with and use on a daily basis; (b) defining attributes for each practice, emphasising the dimensions which were typical of their implementation in LP environments; (c) defining a set of evidence and sources of evidence for assessing the existence of each attribute–the sources of evidence included direct observations, analysis of documents, interviews and a feedback meeting to validate the assessment results with company representatives; (d) drawing up a model of the relationships among the LP practices, based on a survey with LP experts. This model supports the identification of improvement opportunities in MC performance based on the analysis of their interfaces. A case study of an MC from an automobile parts supplier is presented to illustrate the application of the framework.     

Structural Equation Modelling of lean manufacturing practices

The purpose of this research study is to analyse lean manufacturing practices in different industries and to identify the critical factors for its success implementation. Despite the fact that lean manufacturing has been frequently promoted as a means of improving business competitiveness, little empirical evidence exists in the literature validating its positive link with organisational performance. Lean manufacturing practices not only help in reducing the number of defects but also reduces the cost of production. For this purpose, empirical data is collected to measure the lean manufacturing practices prevailing in different industries located in Tamil Nadu, India. A Structural Equation Modelling (SEM) technique is used to build the measurement and structural models. Later, statistical estimates are used to validate the model that has been built. The data analysis helps to determine whether to accept or reject the hypothesis that has been stated based on the structural model. The result shows how lean manufacturing practices are correlated and help in improving the organisational performance among the industries being surveyed.     

Industry 4.0 and lean manufacturing practices for sustainable organisational performance in Indian manufacturing companies

The current literature claims the direct effects of industry 4.0 technologies (I4?T) on lean manufacturing practices (LMP) and sustainable organisational performance (SOP). LMP are also found to have a positive influence on SOP. However, the integrated effect of I4?T and LMP on SOP has not been empirically investigated. To address this gap, this research study investigates the indirect effects of I4?T on SOP with LMP as the mediating variable; furthermore, it aims to confirm or not the direct effects of I4?T on LMP and SOP. The study is based on data collected from 205 managers, working in 115 manufacturing firms. The findings suggest significant direct and indirect effects of I4?T on SOP and confirm the presence of LMP as a strong mediating variable. The results of the study extend the literature on I4?T by identifying I4?T as an enabler of LMP, leading to enhancement of the SOP. Implications and future research directions for academicians, practitioners, and consultants are provided.     

Leanness assessment using multi-grade fuzzy approach

The manufacturing organisations have been witnessing a transition from mass manufacturing to lean manufacturing. Lean operations are characterised by the elimination of obvious wastes occurring in the manufacturing process, thereby facilitating cost reduction. This paper reports a research carried out to assess the leanness of an organisation using multi-grade fuzzy approach. During this research, a leanness measurement model incorporated with multi-grade fuzzy approach was designed. This is followed by the substitution of the data gathered from a manufacturing organisation. After the computation of leanness index, the areas for leanness improvement have been identified. The approach contributed in this project could be used as a test kit for periodically evaluating an organisation's leanness.     

Bayesian Statistical Process Control

This article presents a general Bayesian statistical process control chart. Most previous applications of Bayes' theorem to quality control have either been tied to a rigid optimization model or have used Bayes' theorem to infer the values of structural parameters of the monitored process. The methodology presented differs from both of these approaches. The result is a flexible tool that can be manipulated by decision makers, as is the case with other types of control charts. The Bayesian chart is demonstrated for joint monitoring of the mean and standard deviation of a normal random variable, and compared to both Shewhart and cumulative sum monitoring. The basis for comparison is the expected number of false alarms per expected time in control and the average out-of-control run length. The comparison identifies types of production process where the Bayesian chart has better expected performance than the other two charts and also shows that even though the Bayesian chart requires more detailed knowledge of process structure, acquiring this knowledge can yield real benefits. The article concludes with a practical example.