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.     

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.     

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.     

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.     

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.     

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.     

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。     

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.     

OEE and equipment effectiveness: an evaluation

The overall equipment effectiveness or efficiency (OEE) is a metric that has been accepted in the semiconductor industry. OEE is simple and clear, and standards and guidelines have been developed. Nonetheless, the literature indicates imperfections in applying OEE with regard to the time base and rate efficiency. As OEE lacks a proper framework, the equipment effectiveness (E) has been developed based on a systematic approach to the equipment. E considers the effectiveness of the equipment with respect to availability, speed and quality losses. Unlike OEE, E is a performance measure for stand-alone equipment, isolated from the environment. In addition, E uses the available effective time as a basis in contrast to OEE, which uses the total time as a basis for measurement. Finally, due to the fact that E is measured directly by the production and effective time, it does not depend on the utilization of the equipment, unlike OEE. Furthermore, it has been shown that OEE does not indicate the influence of downtime and rework, whereas E gives these influences correctly.     

复合机铝箔换卷中的速度损失研究

目的减少铝箔复合机换卷时的速度降幅及变化,改善降速换卷中容易断幅的问题,从而提高设备的综合效率(OEE)。方法通过对实验数据的5W1H和张力分析,建立复合机铝箔换卷时铝箔张力的动力模型,探讨了张紧辊张力、压辊压力、铝箔偏心度、运动离心力方向角和速度差等影响铝箔张力的因素,并对实际操进行了实验改进。结果铝箔在换卷时速度变化得到改善,改善了断幅的问题。结论调整影响铝箔张力等一系列因素,综合效率(OEE)达到92.1%,提高了生产效率。     

A synergetic approach for assessing and improving equipment performance in offshore industry based on dependability

The objective of this paper is to present a framework for assessing and improving offshore equipment performance based on dependability. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the equipment performance. The validity of the model is verified and validated by data envelopment analysis (DEA). Furthermore, a non-parametric correlation method, namely, Spearman correlation experiment shows a high level of correlation between the findings of PCA and DEA. The equipment of offshore industries is considered according to OREDA classification. The approach identifies the critical equipment, which could initiate the major hazards in the system. At first PCA is used for assessing the performance of the equipment and ranking them. IA is then performed for the worst equipment which could have most impact on the overall system effectiveness to classify their components based on the component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward decreasing failure interdependency and magnitude of incidents which ultimately maximize overall operational effectiveness.     

Accounting for productivity losses in aggregate planning

The aggregate planning literature fails to account correctly for productivity losses incurred by employee layoffs and hires. Moreover, the literature is mostly silent on the productivity losses associated with other capacity changes such as multiple shifts and overtime. In those cases where productivity losses are considered, traditional approaches impute associated costs but fail to account for lost capacity. It was found that when linear programming formulations have capacity constraints that explicitly account for productivity losses, the resulting production plans are superior to those obtained when productivity losses are modelled solely as costs in the objective function. Some avenues for future research are also proposed.     

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.     

The effect of academic inbreeding on scientific effectiveness

In academia, the term “inbreeding” refers to a situation wherein PhDs are employed in the very same institution that trained them during their doctoral studies. Academic inbreeding has a negative perception on the account that it damages both scientific effectiveness and productivity. In this article, the effect of inbreeding on scientific effectiveness is investigated through a case study. This problem is addressed by utilizing Hirsch index as a reliable metric of an academic’s scientific productivity. Utilizing the dataset, constructed with academic performance indicators of individuals from the Mechanical and Aeronautical Engineering Departments, of the Turkish Technical Universities, we demonstrate that academic inbreeding has a negative impact on apparent scientific effectiveness through a negative binomial model. This model appears to be the most suitable one for the dataset which is a type of count data. We report chi-square statistics and likelihood ratio test for the parameter alpha. According to the chi-square statistics the model is significant as a whole. The incidence rate ratio for the variable “inbreeding” is estimated to be 0.11 and this ratio tells that, holding all the other factors constant, for the inbred faculty, the h-index is about 89% lower when compared to the non-inbred faculty. Furthermore, there exists negative and statistically significant correlation with an individual’s productivity and the percentage of inbred faculty members at the very same department. Excessive practice of inbreeding adversely affects the overall productivity. Decision makers are urged to limit this practice to a minimum in order to foster a vibrant research environment. Furthermore, it is also found that scientific productivity of an individual decreases towards the end of his scientific career.     

State-based analysis of labour productivity

Establishing efficient continuous improvement processes requires industrial companies to analyse their productivity quickly on different work system levels and to link productivity losses with suitable improvement measures in the course of productivity management. Common productivity analyses are either narrowed to certain functions of a production process or they do not possess a sufficient level of detail to derive goal-oriented improvement measures. The challenge is to gain production data with a relatively low effort and to gain broad transparency over productivity losses from the work place to the company level at the same time. This paper presents a new methodology for the comprehensive analysis of the various impacts on labour productivity, relying on state-based modelling of worker activities in serial production. Typical application areas include the automotive industry or the production of home appliances. The approach combines straightforward data acquisition methods with a structured evaluation process as foundation for the productivity management on different work system levels, including work stations, production lines, production segments and the plant. An integrated matching procedure processes the analysis results and yields a set of applicable improvement methods from a definable toolset. Compared with existing methodologies, the underlying model promises a reduced data acquisition effort and high usability. Its potential for practical application is shown with two industrial case studies.     

The refrigerated storage of tropical and subtropical products

During the last few years increased emphasis has been placed on the development of methods for reducing losses of perishable produce after harvest rather than endeavouring the boost production. It has been estimated that 25 to 80% of fresh fruit and vegetables are lost afer harvest. The most serious losses are thought to occur in tropical regions which include a large proportion of the developing countries. Even in developed countries postharvest losses can be substantial.

Provided that produce has been harvested at the best stages of maturity and handled carefully, refrigeration offers the greatest potential for increasing postharvest life. However, refrigeration is expensive and many sub-tropical and tropical species are sensitive to chilling. For these species the benefits of refrigeration are limited. Research is proceeding along two principal lines. One line involves the study of the basic differences between closely related species which differ greatly in sensitivity to chilling. It is hoped that knowledge of the nature of chilling injury will assist in the development of methods for overcoming or ameliorating chilling injury thereby increasing the effectiveness of refrigerated storage. The second line of research is concerned with developing techniques for extending post-harvest life with a minimum of refrigeration. Results of these lines of research will be discussed.     

Use of chloride-based ice control products for sustainable winter maintenance: A balanced perspective

Drawing upon relevant literature, this work explores various dimensions of using chloride-based ice control products for winter maintenance operations. Winter maintenance operations play an important role in assuring the safety, mobility and productivity of roadways enduring wintery weather. Traditionally, nominal cost and effectiveness are the major criteria when highway professionals select the chemicals for snow and ice control. However, there are growing concerns over negative impacts that chloride-based ice control products pose on motor vehicles, the transportation infrastructure, and the environment. The authors propose that the use of chloride-based products for sustainable winter maintenance necessitates the application of a balanced perspective and collaborative decision-making among all relevant stakeholders. The shortcomings of existing maintenance decision systems are discussed, followed by a new way of thinking under the asset management framework.