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.     

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.     

Energy efficiency analysis of machine tools with periodic maintenance

Machine tools consume a large amount of energy in the production process. Effective reduction of energy consumption of the machine tool will lead to significant savings. Although substantial efforts have been devoted to reducing energy consumption of the machine tool through upgrading the equipment or improving the manufacturing process, the study of energy efficiency improvement through effective maintenance operations scheduling has received significantly less attention. Power consumption usually increases as the machine tool deteriorates in most mechanical manufacturing environments. In this paper, we develop a discrete-time, discrete-state homogeneous Markov chain of the deteriorating machine tool based on energy efficiency. To evaluate the energy performance and productivity performance of the machine tool with periodic maintenance, analytical models of average energy efficiency and average productivity are developed based on renewal reward theorem. The effects of some parameters on the average energy efficiency are analysed through a numerical example, and the trade-off between energy efficiency and productivity is discussed.     

Production management model integrating the principles of lean manufacturing and sustainability supported by the cultural transformation of a company

The search for superior production performance has been used by companies to overcome competition in the current global economic scenario. Efficient manufacturing connected to environmental initiatives provides a company with favourable conditions for maintaining uniform and continuous improvement in its competitive performance, while providing operational versatility to respond quickly to volatile markets. As production is one of the most expensive areas for a company, many organisations have sought a new management model for their production system that provides substantial productivity gains, cost saving opportunities and higher customer satisfaction. This study proposes a model of production management and an implementation method integrating the principles of lean manufacturing and sustainability, supported by cultural transformation at the company. Its objective was to achieve productivity gains and improvements on customer satisfaction, as well as develop the ability to provide quick responses to market changes in a globalised economy. The implementation of the proposed model should be gradual, initially addressing fundamental principles, and should operate simultaneously with, and in the same environment as, workforce development and organisational transformation initiatives, to create sustainable improvements.     

Manufacturing productivity improvement using effectiveness metrics and simulation analysis

Traditional productivity metrics, such as throughput and utilization rate, are not very helpful for identifying the underlying problems and opportunities for productivity improvement in a manufacturing system. In this paper, a systematic methodology is presented for productivity measurement and analysis at the factory level. Metrics of Overall Equipment Effectiveness (OEE) and Overall Throughput Effectiveness (OTE) are introduced and developed, respectively, for rigorous and quantitative measurement of equipment and system productivity. These metrics are integrated with computer simulation to facilitate rapid analysis of equipment and manufacturing system productivity, and the investigation of productivity improvement opportunities. The results of this research make possible the representation of factory level productivity or overall factory effectiveness by OTE, and the use of OTE for quantitative benchmarking and comparison of the productivity of various factories. A real-world manufacturing case study is reported to demonstrate how to employ these techniques to improve manufacturing productivity.     

卷包机组设备效率评价指标体系的设计与实现

目的 针对烟草行业常见设备卷包机组,提出一种结合OEE的设备效率评价体系,实现对卷包机组设备运行状态的精确、实时、具体的反映.方法 通过分析离散制造与连续制造的差异,在传统离散制造OEE方法基础上,针对连续生产进行适应性改进,提出一套针对卷包机组的设备效率评价指标;在此基础上,通过分析卷包机组各运行单元结构特点,提出一套实时采集设备状态数据与动态分析效率状态的卷包机组设备效率评价体系.结果 将此体系部署于湖北中烟某车间6台卷包机上6个月进行实验验证,结果显示在该体系的支持下,设备净效能平均同比增长7.72％,证明本效率评价结果可以精准、全面、实时地反映设备运行情况和状态背后的影响因素,有助于提升卷烟机组设备效率.结论 文中提出的卷包机组设备效率评价指标体系使用户可以针对性、快速地调整设备运行状态,实现了精准管理,提高了生产作业效率,具有实际的推广价值.     

Comparing manufacturing output and practices in China,Hungary, the USSR and USA

This paper explores the sales productivity of manufacturing companies in four countries. Specifically, data envelopment analysis (DEA) is used to compare the use of labour and equipment to produce domestic and export sales in the People's Republic of China, Hungary, the USSR (before the break-up of the republic) and the United States. Firms from the machine tool industry were evaluated using data gathered by the Global Manufacturing Research Group. When labour hours and equipment are considered, the United States’ firms are the most efficient at producing sales output and China's firms the least. When labour dollars instead of labour hours are considered, surprisingly, China's firms remain least efficient while those from the USSR and Hungary fare quite well when compared with those from the United States. Several important differences in manufacturing practices help explain the differences in sales productivity and point out areas where care must be taken in creating joint ventures between firms in these countries.     

维修管理模式对制造企业质量控制影响的实证研究

可靠的设备预防维修水平和卓越的产品质量保证能力是保障产品过程质量的关键,现有多数研究集中在质量管理模式与企业绩效的关系分析。在对过程质量控制、设备维修管理评述的基础上,探讨了设备维修管理模式与维修绩效及过程质量控制绩效间的关系。以国内制造企业的连续生产方式为研究对象,运用结构方程模型剖析了RCM、TPM、设备采购管理与和设备维修绩效、过程质量控制绩效的路径关系,发现基础维修管理活动对维修绩效有间接影响,RCM、TPM对设备维修绩效有显著影响,路径系数分别为0.346、0.717,设备维修绩效对过程质量控制绩效的影响显著,路径系数为0922。证明制造企业为提升产品质量,需要完善其设备预防维修系统。     

Overall throughput effectiveness (OTE) metric for factory-level performance monitoring and bottleneck detection

Seiichi Nakajima provided overall equipment effectiveness (OEE) to measure productivity and perform diagnostics at the equipment level. However, a literature review indicates that such metrics are lacking at the factory level. In order to address this gap, an overall throughput effectiveness (OTE) metric is developed. The purpose of OTE is twofold: it measures factory-level performance and can also be used for performing factory-level diagnostics such as bottleneck detection and identifying hidden capacity. The task of coming up with such a metric was achieved by defining a set of commonly occurring predefined subsystems including series, parallel, assembly and expansion. OTE was developed for each of these predefined subsystems. It also accounts for subsystems processing multiple products and performing rework. Any factory layout can be modelled using a combination of the predefined subsystems, which allows determination of the overall factory effectiveness (OFE). More importantly, OTE has the potential to automate the entire factory-level performance diagnostics, hence drive continuous productivity improvement quantitatively. This paper explains the OTE development methodology, validates the developed OTE metrics and demonstrates its diagnostic ability. Application of OTE to a wafer fab and glass manufacturing case study showed that productivity bottleneck and opportunities for improvement can be identified quantitatively.     

Stochastic overall equipment effectiveness

This article focuses on the overall equipment effectiveness (OEE), a key performance indicator typically adopted to support Lean Manufacturing and Total Productive Maintenance. Unfortunately, being a deterministic metric, the OEE only provides a static representation of a process, but fails to capture the real variability of manufacturing performances. To take into account the stochastic nature of the OEE, an approximated procedure based on the application of the Central Limit Theorem is presented: the OEE is considered as a stochastic random variable and its probability density function (pdf) is generated through the aggregation of the pdf of the basic causes of waste. Notwithstanding its approximated nature, the procedure can be applied in most practical cases, since the accuracy is assured provided that the average OEE is lower than 90% and the variability of the losses is high. The validity of the approach has also been confirmed by an industrial application included in this article. The results obtained demonstrate that the stochastic OEE can help in battling variation, for it allows one to identify the hidden losses that account for most of the variability and to estimate the impacts of potential corrective actions in terms of both efficiency and efficacy.     

A developed autonomous preventive maintenance programme using RCA and FMEA

Total productive maintenance (TPM) was developed in Japan in 1971 and has since been phased into many manufacturing firms to promote productivity and competitiveness. Autonomous preventive maintenance (APM) systems are very special. The fundamental pillar of TPM includes a series of important systematical first-line direct labour activities. The technical cost, human resources and management issues are all considered. Failure modes and effects analysis (FMEA) and root-cause analysis (RCA) are the most popular failure analytical methods, widely adopted over different industries. They are often used to examine the potential problems in the design and manufacturing phase, discovering possible failure causes before product design and manufacturing finalisation. This study integrates the RCA and FMEA techniques to establish an APM system that meets a company’s goal of reducing manufacturing costs and promoting employee and equipment productivity. The major contribution of this study is constructing potential equipment failure modes and their risk priority number through RCA and FMEA integration transformed into a selection of items and their APM maintenance frequencies. A strategy for deploying employee technical capability upgrade through effective training is developed. This study uses the S Company – a key manufacturer of semiconductor material – as a case study to verify the model’s applicability and suitability.     

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。     

Cost modelling in polymer composite applications: Case study – Analysis of existing and automated manufacturing processes for a large wind turbine blade

Cost modelling is typically one of the first steps in the design and development of a new or existing product and can show clear avenues for effective manufacturing. This paper provides an overview of existing cost modelling techniques and details the process term technical cost modelling (TCM), which is a combined parametric and process flow simulation method used widely throughout the manufacturing industry where historical data is either not available or does not exist. A focus is drawn on the manufacture of a 40 m wind turbine blade with the effects of part size, production volume, materials costs and tooling being detailed. A case study is presented which investigates the cost effectiveness of a range of existing manual production methods (hand-lay prepreg, VI, LRTM) and compares this to automated manufacturing (ATL, AFP, overlay braiding). ATL and AFP are shown to reduce manufacturing costs by up to 8% despite the high capital costs associated with automated equipment. The cost centres are isolated and clearly indicate the dominance of materials and labour. Material deposition in the tool is only one of a string of labour intensive processes in the manufacture of a large wind turbine blades and a holistic automated blade manufacturing approach is perhaps required to see the true labour saving benefits.     

Facility layout optimization using simulation and genetic algorithms

Traditionally, the objective of a facility layout problem has been to minimize the material handling cost of the manufacturing system. While it is important to reduce the amount of material handling, the traditional methods do not address the actual time at which the material is transported. In today's short cycle time production environments, the timing of material movement may have a bigger impact on the productivity of the system than its cost. In this paper, a facility layout optimization technique is presented that takes into consideration the dynamic characteristics and operational constraints of the system as a whole, and is able to solve the facility layout design problem based on a system's performance measures, such as the cycle time and productivity. Each layout solution is presented in the form of a string that is suitable for analysis by a genetic algorithm technique. These solutions are then translated into simulation models by a specially designed automated simulation model generator. Genetic algorithms are used to optimize the layout for manufacturing effectiveness while simulation serves as a system performance evaluation tool. Combined with a statistical comparison technique to reduce the simulation burden, the test results demonstrate that the proposed approach overcomes the limitations of traditional layout optimization methods and is capable of finding optimal or near optimal solutions.     

Manufacturing planning and control approaches: market alignment and performance

The design of manufacturing planning and control (MPC) systems is a strategic decision for manufacturing operations. In this paper we analyze the interrelationships between the choice of MPC approaches at different hierarchical levels with market requirements and operational performance. These relationships are explored through an extensive survey comprising responses from 128 manufacturing firms. The results show that the choice of MPC approaches, primarily at the sales and operations planning and master scheduling levels, has a significant mediating role in improving performance. The alignment between market requirements and the choice of MPC approaches is significant and has a significant impact on performance. In a dynamic environment, the choice of MPC approaches is shown to have a positive mediating effect on operational performance.     

Group technology in the US manufacturing industry: A survey of current practices

This paper reports the findings of a survey of 53 US users of group technology (GT). Respondent installations were medium to large electronics and metalworking manufacturers. They engaged predominantly in fabrication activities, producing a large number of component parts and/or end items. These firms applied GT to design, process planning (including NC programming), sales, purchasing, cost estimation, tooling, scheduling, new equipment sizing, and tool selection. In the majority of cases, firms used classification and coding systems as tools in applying GT. While users identified managerial and technical barriers which must be overcome in successfully applying GT, significant and varied operational and strategic benefits had been achieved. Further, most felt that GT would be an integral and important part of future CAD/CAM activities at their plant. The respondents' experiences confirm that GT's usefulness is quite broad and suggest that failure to understand GT as a general philosophy and, instead, to consider it a tool or equate it with a specific use, may result in lost opportunities to improve manufacturing productivity. A second paper, based on the same survey data, describes these manufacturers' experiences with cellular manufacturing (Wemmerlov and Hyer 1989).     

Profit loss indicator:a novel maintenance indicator applied for integrated planning

In production environment today,"silo thinking"is a challenge where controlling an asset associated with several disciplines and departments can lead to a suboptimal result.This requires a more integrated approach with an integrated planning(IPL)framework.In this framework novel maintenance key performance indicators(KPIs)are needed.The purpose of this article is to develop the novel maintenance KPI profit loss indicator(PLI).This indicator is based on measuring both on the"hidden factory"and waste in production,presenting it as a financial measure.The notion"hidden factory"is used as a metaphor for measuring the time losses in industry through the maintenance KPI overall equipment effectiveness(OEE).This indicator divides the time losses into availability losses,performance losses and quality losses.In addition,a financial measure for waste based on literature from Toyota production system(TPS)and waste treatment and disposal is also included in PLL Through a case study in the saw mill industry PLI is demonstrated and evaluated.It is expected that this indicator will be demonstrated in several industry branches in the future.     

Integrating Six Sigma Culture and TPM Framework to Improve Manufacturing Performance in SMEs

Worldwide, small and medium enterprises (SMEs) have been accepted as the engine of economic growth, especially in the emerging economies, and for promoting equitable development their contribution as a component to nation's infrastructure is relatively high. Global competition forces SMEs to improve their competitiveness by enhancing their manufacturing performance. Hence, they have to pay attention to the reliability of their production processes as well as their commitment to quality management practices. In present times, because of automation and large‐scale mechanization, higher plant availability, better product quality and longer equipment life had assumed considerable significance among the SMEs. In order to meet the above challenges, adoption and practice of proactive maintenance strategies along with execution of best management practices, i.e. lean Six Sigma (LSS), has become essential for organizations to bring down maintenance and production costs. As evident from literature, both total productive maintenance (TPM) and Six Sigma are key business process strategies employed by SMEs to enhance their manufacturing performance. However, whilst there is significant research information available on implementing these systems in an independent manner, there is little information available relating to the integration of these approaches to provide a unified and highly effective implementation framework. The purpose of this paper is thus to develop an integrated model based on Six Sigma and TPM framework focusing on adding performance indicators. The goals of the study were achieved by utilizing various tools such as ‘brainstorming sessions, pareto analysis fish‐bone diagrams, histograms, FMEA, box plots, control charts and process capability plots for analysis’. While implementation of such twin framework requires greater management commitment in terms of training, resources and integration, they are also expected to provide higher levels of equipment and plant performance as evident from the results. The results show significant improvement in OEE level (Before 50, 54 and after 76, 83 for M/C –I and M/c‐II), reduction in rework (from 22% to 10%), reduction in maintenance versus operation cost (from 30% to 10%) and reduction in defect rate (from 24.82% to 5%) and average outgoing quality level (from 30% to 5%). The substantial improvement in sigma level from 2.16 and 2.64 to 4.01 and 4.12 for M/C –I and M/C‐II resulted in financial savings of approximately $2 m per annum. Copyright © 2013 John Wiley & Sons, Ltd.