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The purpose of this paper is to describe the overall equipment cost loss (OECL) methodology and an implementation of this methodology, to compare the outcomes of OECL with those of overall equipment effectiveness (OEE), and finally to identify the benefits offered by this new methodology.

The proposed methodology, OECL, combines six large loss models and a financial model in the performance evaluation of equipment. The six large losses are converted into monetary units. OECL is a new way of evaluating equipment performance that differs from the original OEE methodology and overcomes some of the limitations of OEE. This new methodology can be used to rank problematic machines by accounting for production elements together with finance elements.

The OECL and OEE methodologies rank problematic machines differently.

Efforts were made in this research to identify factors affecting OECL outcomes, but it was found that it was not possible to apply OECL to all scenarios.

The OECL model can be implemented in a real manufacturing company to help decision-makers better determine the magnitudes of equipment problems and rank problematic pieces of equipment appropriately.

This OECL method is able to overcome some of OEE’s weaknesses. It can properly prioritise problematic machines by considering both cost and losses.

Overall equipment effectiveness (OEE) is a metric for estimating equipment effectiveness of the industrial systems. The purpose of this paper is to identify maintenance improvement potentials using an OEE assessment within the croissant production line.

The present work is carried out by analyzing the failure and repair data of the line. The failure data cover a period of 15 months. During this period the croissant production line usually operates over the entire day (24 h per day) in three 8-h shifts per day, and pauses at the weekends. Descriptive statistics of the failure and repair data for the line based on scheduled and unscheduled interruptions were carried. Moreover, the actual availability (A), performance efficiency (PE) and quality rate (Q) measures, together with the complete OEE for each working day for the croissant production line, were shown.

The main objectives are to understand the operation management of the croissant production line, and to measure the OEE characteristics in precise quantitative terms. OEE analysis can help the company to identify the primary problems concerning the A, PE and Q and acts immediately.

This paper presents a successful evaluation of OEE which will provide a useful guide to aspects of the production process, which identifies the critical points of the line that require further improvement through effective maintenance strategy (i.e. total productive maintenance). Moreover, the analysis provides a useful perspective and helps managers and engineers make better decisions on how to improve manufacturing productivity and quality.

The overall equipment effectiveness (OEE) is a powerful metric in production as well as one of the methods in evaluating function for measuring productivity in the production process. In the existing method, measuring OEE is based on three main elements consisting availability, performance and quality. The purpose of this paper is to evaluate the recognized metrics of production: OEE and overall line effectiveness (OLE) by using smart systems techniques.

In this paper, to improve the calculative methods and productivity with three methods: measuring OEE using Mamdani fuzzy inference systems (FIS), measuring OEE using Sugeno FIS, and measuring OLE using FIS and artificial neural networks (ANNs) are proposed.

The proposed methodologies aim to decrease some weaknesses of OEE and OLE methods by exploiting intelligent system techniques, such as FIS and ANNs. In particular, this research will solve the following issues that occur in manual and automatic data gathering. This technique is an effective way of measuring OEE and OLE with regard to different weights of losses as well as difference in the weight of the machines. In addition, it allows the operator’s knowledge to take a part in the measurement using uncertain input and output with implementation of linguistic terms. The presented method is the details and capabilities of those methods in various tested scenarios, and the results have been fully analyzed.

In relation to other methodologies, it allows the operator’s knowledge to take part in the measurement using uncertain input and output with implementation of linguistic terms. The presented method is the details and capabilities of those methods in various tested scenarios, and the results have been fully analyzed.

The purpose of this paper is to develop a novel training material for the performance indicator overall equipment effectiveness (OEE) in the form of a game-based learning (GBL) approach to be used in Industry and University context. The paper will present the development of the game as well as results from tests of the game with Industry employees and University students.

The data that are used in the game have been acquired from real OEE data logs of a reference company. The game has been refined iteratively using feedback from the participants of the tests.

The paper presents the game with its components and learning objectives. A comparison of various theoretical factors on GBL and the novel training material is performed and future improvements are suggested.

The game has been developed based on OEE data logs from only one reference company.

The training material and specifically the game can be used to train Industrial workers and University students to better envision OEE as a performance indicator.

Serious games on lean manufacturing have been developed and played for a long time. While some of these games include OEE as an important result parameter, none really demonstrates how it is measured and analyzed.

The purpose of this paper is to introduce a practical integrated overall equipment effectiveness (OEE) framework that encompasses the core characteristics of OEE.

The paper reviewed the backgrounds of OEE and improvement frameworks and explored the limitations. An integrated OEE framework was developed by synergizing the strengths of OEE and improvement frameworks to complement the shortcomings. This new framework underlies the OEE concepts and provides structural improvement steps. It was applied to systematically assist and guide OEE practitioners in a case study.

The review of OEE literature found that there is a lack of improvement frameworks with systematic steps specifically developed for OEE implementation. Conversely, a review on improvement frameworks of different methodologies revealed that they do not fully capitalize on the use of performance measures as benchmarks and improvement drivers. An integrated framework that incorporated the advantages of both OEE and conventional improvement frameworks was developed and validated through a case study over a period of 38 weeks. The OEE performance before the improvements was low (73.4 percent) due to high availability losses (76.5 percent). Both OEE and availability achieved the target of 76.5 percent and 80 percent, respectively, after using the framework for improvements.

The reviewed papers represent a sample of papers present in the literature and were selected based on relevancy. A greater number of papers incorporated into the literature review would certainly bring out a more comprehensive study.

The proposed integrated OEE framework provides OEE practitioners with systematic directions and steps combined with benchmarking and loss prioritization features for effective improvement efforts. In addition, it provides overview for the practitioners to make better decisions in project management. This helps address the common issues of practitioners not sure of what the next improvement step is. A case study using the proposed framework at a semiconductor company had successfully achieved the OEE benchmarks and set target for conversion time.

This paper provides a new integrated OEE framework offering a systematic approach toward implementing OEE improvements.

This study provides a unique integrated diagnosis system to investigate the causes of low productivity, profitability, machinery health conditions and wear severity of medium-size biscuit industry assets in Taiz, Yemen.

The evaluation is based on an integrating of the overall equipment effectiveness (OEE) and oil-based maintenance (OBM) approaches. The data are collected using the company's operational records, interviews and observations, while the used lubricating oil samples are also collected from production lines' machineries. Scanning electron microscope (SEM) is used to study the wear debris particle features and wear mechanism. Different other analysis tools such as fishbone, 5 whys and Pareto charts are also used to investigate the root causes and plausible recovery solutions of machinery failures.

This study demonstrated that a large proportion of machinery failures and production loss are of management concerns. Also, this study inferred that the analysis of wear debris is unique and informative for determining machinery wear severity and useful life. Finally, the current conditions of production lines are clarified and suggestions to use a mixed preventive/predictive maintenance management approach are also elucidated.

This work implemented an integrated OEE/OBM diagnostic maintenance system to investigate the root causes of low productivity and machine failures in real production lines and suggested robust decisions on the maintenance duties.

With the growing importance of performance measurement and management, this exploratory study intends to examine the practices of maintenance managers with regards to maintenance measures, as used in their organizations. In this process, the study attempts to uncover the relevant maintenance performance dimensions from the perspectives of the surveyed managers. In addition, the mediating effect of information availability on the main performance measures utilization is studied.

The research at hand is survey-based. It utilizes the responses of a sample of ninety-five (95) experienced maintenance managers to identify the most relevant maintenance performance measures. Factor analysis is then utilized to uncover the important dimensions of performance, as seen by the respondents. Additionally, using the Partial Least Squares method, several models were studied.

The findings of this exploratory research appear to suggest that maintenance managers are beginning to broaden their perspective with regard to performance management. While machine and plant-related performance measures are still emphasized, maintenance managers are slowly moving toward a wider organizational orientation. While the manufacturing organizations are becoming more and more customer-oriented open systems, the maintenance function of these organizations is still, for the most part, operating under the semi-open system orientation. Overall, it appears that an emerging maintenance strategy is slowly taking shape.

For the most part, performance measures and measurement related to maintenance have not received enough attention from researchers. Therefore, the literature dealing with the different facets of performance in maintenance has not been forthcoming. The study attempts to fill this apparent gap in the literature. This is important, as maintenance managers are being asked to contribute to the achievement of the competitive strategies of their organizations. Therefore, they must quickly learn how to view maintenance from a coherent strategic organizational perspective. Such a perspective should help in integrating the maintenance, resources, capabilities, and technical know-how in order to serve the strategic goal of their organization. The research at hand is limited to a sample from Portugal. Therefore, the results and conclusions must be interpreted accordingly.

As maintenance managers struggle to move from a machine-orientation to a more organizational-wide strategic orientation, they are often left with many questions and few answers. This study attempts to bring this problem to the spotlight so that it can receive more systematic empirical and practical research. In this context, the role of maintenance managers in the process of organizational strategy formulation should be examined.

The study presented in this article has practical, as well as theoretical contributions. It deals with an area of performance measurement, which so far has been relatively ignored. It uses a system orientation (closed vs open), in addition to the strategic orientation (single vs multi-faceted strategy) in order to shed some light on the need to have consistency between the nature of the system and its strategic objective.

The purpose of this paper is to examine the longitudinal evolution of quality costs measurement, depicted in 99 real data studies of the last 30 years. A meta-analysis of these articles is conducted, in order to highlight the evolution of the variables that have been used for the study of quality costing, in relation to the date of publication, business sector and geographical origin of each paper.

The analysis of the cost components has been conducted with the use of multiple correspondence analysis, which is a useful tool for the exploration of the interrelations among all elements, aiming at the identification of the dominant and most substantial tendencies in their structure.

The findings suggest that the level of analysis of quality costs is related to the date of publication, the business sector and the origin of each research. Furthermore, it is pointed out that the most prominent prevention costs are related to suppliers’ assurance, internal audit and new product’s design and development. Appraisal costs are mostly defined by quality audits and procurement costs, while failure costs by defect/failure analysis, low quality losses, complaint investigation and concessions and warranty claims.

The present paper is a longitudinal meta-analysis of 99 quality cost papers that have been published in the last 30 years. It explores the evolution of research in quality costing, not only in relation to the cost components in use, but also in terms of date of publication, business sector and geographical origin of the studies.

The purpose of this paper is to review the literature on Total Productive Maintenance (TPM) and to present an overview of TPM implementation practices adopted by the manufacturing organizations. It also seeks to highlight appropriate enablers and success factors for eliminating barriers in successful TPM implementation.

The paper systematically categorizes the published literature and then analyzes and reviews it methodically.

The paper reveals the important issues in Total Productive Maintenance ranging from maintenance techniques, framework of TPM, overall equipment effectiveness (OEE), TPM implementation practices, barriers and success factors in TPM implementation, etc. The contributions of strategic TPM programmes towards improving manufacturing competencies of the organizations have also been highlighted here.

The literature on classification of Total Productive Maintenance has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of various TPM implementation practices demonstrated by manufacturing organizations globally. It also highlights the approaches suggested by various researchers and practitioners and critically evaluates the reasons behind failure of TPM programmes in the organizations. Further, the enablers and success factors for TPM implementation have also been highlighted for ensuring smooth and effective TPM implementation in the organizations.

The paper contains a comprehensive listing of publications on the field in question and their classification according to various attributes. It will be useful to researchers, maintenance professionals and others concerned with maintenance to understand the significance of TPM.

As overall equipment effectiveness (OEE) is a metric to estimate equipment effectiveness of production systems, the purpose of this paper is to identify strategic management tools and techniques based on OEE assessment of the ice cream production line.

This paper presents the collection and the analysis of data for ice cream production under real working conditions. The data cover a period of eight months. A framework process to improve the OEE of an automated production system was proposed. Six major stoppage losses, i.e. equipment failure, setup and adjustment, idling and minor stoppage, reduced speed, defects in the process, and reduced yield, were examined with the help of Pareto analysis. In addition, the actual availability (A), performance efficiency (PΕ) and quality rate (QR) measures, together with the complete OEE for each working day, week and month of the production line were shown.

The main goal of the study is to identify major stoppage losses, in order to examine and improve the overall equipment efficiency (OEE) of the ice cream production line through the application of an adequate management, i.e. TPM approach. Based on the obtained results, maintenance management strategy and production planning have been suggested to improve their maintenance procedures and the productivity as well.

The proposed method can be applied to each automated production system. The main benefits of this method are the improvement of productivity, quality enhancement of products, the reduction of sudden breakdowns and the cost of maintenance. Moreover, the analysis provides a useful perspective and helps managers/engineers make better decisions on the operations management of the line, and suggestions for improvement were proposed and will be implemented accordingly.