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From both economic as well as environmental perspective energy demand is of strong and even more increasing relevance for manufacturing nowadays. But typically energy demand and manufacturing system performance (e.g. output, time demands, quality) are considered separately while actually being inherently connected in technical systems. Against this background, the paper presents a data-based approach to analyze and model those important aspects and interdependencies in an integrated manner. The developed theoretical framework and defined methodology enable deeper understanding of energy related impacts of operative influencing factors and eventually to derive fields of action for improvement. The approach was exemplary applied in an industrial case study. Results underline the feasibility, applicability, and potential benefits of the approach. [ABSTRACT FROM AUTHOR]

In the dynamic landscape of the automotive industry, operational efficiency is a pivotal factor for sustained growth. This study delves into the intricacies of enhancing manufacturing operations, mainly focusing on the blowing machines at RMA Ltd, a key player in the Indonesian automotive SME sector. The primary objective is to optimize Overall Equipment Effectiveness (OEE) by implementing a Total Productive Maintenance (TPM) approach. The Indonesian automotive sector, vital to national economic growth, needs help maintaining optimal production efficiency. This study centres on the blowing machines at RMA Ltd's Plant 7, emphasizing the need to address breakdowns, particularly in the blowing machine, which has been identified as the primary source of production losses. A comprehensive research methodology is outlined, beginning with an extensive literature review on TPM and OEE. The study then focuses on the Indonesian automotive SME sector, with RMA Ltd as the primary research subject. Data collection involves an initial survey to assess the current state of blowing machines, encompassing OEE, Six Big Losses, and other relevant factors. Post-implementation of improvements, the study reveals substantial enhancements in OEE. Availability rates increased (93.19%), Performance Efficiency improved (84.84%), and Quality Rate remained consistently high (98.41%). The calculated OEE rose from 67.42% to an impressive 77.80%. Noteworthy reductions in Six Big Losses, particularly in breakdowns, setup losses, and reduced speed losses, validate the efficacy of TPM implementation. This research introduces a novel approach by integrating socialization strategies, detailed work instructions, and proactive maintenance practices. Through a comprehensive research methodology, including an initial survey and post-implementation analysis, this study demonstrates significant OEE improvements of 11%. The findings underscore the novelty of this research in emphasizing the importance of holistic TPM implementation strategies in enhancing manufacturing operations within the Indonesian automotive SME sector. Furthermore, this study provides actionable insights for SMEs in the Indonesian automotive sector, highlighting the relevance of TPM in achieving operational excellence and competitive advantage. Ultimately, this research contributes a valuable blueprint for SMEs seeking to navigate the complexities of the automotive industry, offering a roadmap to optimize manufacturing operations and thrive in a competitive market. [ABSTRACT FROM AUTHOR]

In today's dynamic business environment, achieving and sustaining operational efficiency is paramount for organizations. To remain competitive and meet evolving customer demands, companies strive to optimize their operations and enhance efficiency. Over time, various indicators have been developed to assess efficiency across multiple operational dimensions, aligning with technological advancements and industrial practices. One such indicator is Overall Equipment Effectiveness (OEE), which evaluates equipment efficiency based on availability, performance, and quality. However, with the advent of the digital industry, the management of data for efficiency calculations has become increasingly complex. In this context, this paper proposes a digitized, real-time OEE calculation system that leverages advanced technologies to continuously monitor OEE, enable real-time decision-making, and drive performance improvements. Harnessing the potential of digitalization, the system facilitates seamless data collection, analysis, and reporting while automating manual processes. By focusing on OEE as a comprehensive efficiency indicator, the proposed system aims to enhance organizational performance and establish a foundation for calculating other efficiency measures. [ABSTRACT FROM AUTHOR]

In recent years, the increasing demand for autonomous vehicles in the mining industry has led to a greater focus on integrating these solutions with mine design. As technology advances, mining companies are looking to maximize the benefits of automation in terms of efficiency, productivity, and safety. The adoption of autonomous vehicles in mine design allows for the optimization of planning and operation of mining activities. Autonomous equipment can work continuously, reducing downtime and improving resource utilization. This has a direct impact on the overall equipment effectiveness (OEE), as availability and performance are significantly enhanced. In this research, the overall equipment effectiveness (OEE) of an Autonomous Haulage System (AHS) and its impact on the design of an open-pit mine were evaluated at the engineering level in Chile. Additionally, a representative month of operation (January 2034) was modeled using discrete event simulation technique with current operation and AHS philosophies. The results of this model, which were validated and calibrated based on historical information, meetings with different work groups, and understanding of the engineering level of the study, indicate that the OEE of manual operation is 14.4% lower than that of AHS operation, demonstrating an opportunity for the implementation of this technology. [ABSTRACT FROM AUTHOR]

The performance of a production work center can be measured in the five dimensions speed, quality, flexibility, dependability, and cost. Existing approaches such as the Overall Equipment Effectiveness (OEE) are either not covering all objectives or give only limited support for full utilization of the increasing amounts of available data in production. This article introduces a hierarchical status classification system that allows the integration of versatile and detailed data streams based on time series. Based on the classifications, a detailed calculation and visualization of work center performance indicators is introduced to support the prioritization of countermeasures for work center's performance increase. [ABSTRACT FROM AUTHOR]

This paper elaborates the manufacturing process and efficiency in detail -- what influenced the production systems in the past but also what they expect in the future. Also, the individual criteria according to which we can break down the production and the factors acting on it. The main efficiency calculation technique is the overall efficiency of the OEE (Overall Equipment Effectiveness) and its extension. There are clearly defined terms such as productivity, efficiency and effectiveness. The aim of this work is to make surface treatments more efficient, to increase savings and productivity. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to determine the methodology for assessing key factors that affect the quality and efficiency of a flexographic printing process. The subject of theoretical considerations is quality evaluation and basic information about efficiency method evaluation, like OEE, SMED and other. The article also presents an evaluation survey of the quality level of printing requirements for customers, conducted by the author. The presented results reveal that those methods are suitable as advanced tools for measuring the quality and efficiency level of manufactured products and the production processes, which also improve customer satisfaction. [ABSTRACT FROM AUTHOR]

The current levels of competition makes the organizations to continually strive to meet the customer demand but it has been observed that due to problems like machine breakdown, machining and setting process delays it has become difficult in meeting this on time. The objective of this article is to inspect the manufacturing losses arising on account of such problems by prioritizing the root causes with the help of a pareto diagram and finally suggesting the solution to overcome these problems. A case study was carried out to improve the utilization of machine tool and manpower by initiating the practices through, TPM that would also form as a base for lean manufacturing. TPM helps to adopt a systematic work inside the shop floor which reduces the losses in production activity, increases the equipment life, ensures effective utilization of equipments and organized employee behavior. Introduction of new fixture reduces the idle time of machine during component setting and achieving cycle time reduction by analyzing cutting tool and its parameters which helps to increase the output to meet the customer demand. From the final results, it was observed that there was reduction in setup time, cycle time, breakdown losses and rework time, while the overall equipment effectiveness was also found to have increased by about 15%. [ABSTRACT FROM AUTHOR]

This work presents an approach to determine relevant energy efficiency and productivity KPIs of machining processes based on a real-time interpretation of sensor data and machine control data. A comparison of the actual power consumption during machining with an energetic model of the load-free condition enables the calculation of energetic efficiency and primary processing time. The approach was tested on a CNC turning and milling center equipped with power meters and compressed air sensors. Sensor data as well as relevant machine control data are read, processed and recorded via SCADA software in order to automatically calculate certain KPIs. [ABSTRACT FROM AUTHOR]

This work presents an approach to determine relevant energy efficiency and productivity KPIs of machining processes based on a real-time interpretation of sensor data and machine control data. A comparison of the actual power consumption during machining with an energetic model of the load-free condition enables the calculation of energetic efficiency and primary processing time. The approach was tested on a CNC turning and milling center equipped with power meters and compressed air sensors. Sensor data as well as relevant machine control data are read, processed and recorded via SCADA software in order to automatically calculate certain KPIs. [ABSTRACT FROM AUTHOR]

Multi-layer Stream Mapping (MSM) comprehends a new framework for the performance assessment of complex systems. The MSM was developed for multi-domain analysis in an original manner to assess if resources, process and other domains are used to their full potential. The costs related with misuses/inefficiency situations are also quantified and integrated in a simplified manner. A real case study applying the MSM method is validated through application to a Medium Density Fibreboard (MDF) finishing line. For this study all the resources and materials consumed in each unit process where considered. The overall efficiency was assessed and improvements actions were evaluated. [ABSTRACT FROM AUTHOR]

Nowadays, many water treatment plants face the problems of equipment breakdown and water loss during water production process. A method to solve these problems is to implement Eight pillars strategy (EPS), one of Total Productive Maintenance (TPM) strategy to reduce equipment breakdown, decrease water loss and enhance equipment effectiveness. Failure rate (FR), availability (A), performance efficiency (PE), quality rate (QR) were determined by evaluating equipment effectiveness through Overall Equipment Effectiveness (OEE). They were also evaluated to find the entire equipment/plant effectiveness through Net Equipment Effectiveness (NEE). In this study, the chlorinator machines in each couple phase 1&2 and 3&4 at Mahasawat Water Treatment Plant (MHS) were considered as a case study for practicing EPS. The reduction of FR and increase of A, PE and QR were revealed after practicing EPS to chlorinators as evidently evaluated in this paper. They affect to higher OEE and NEE in all couple phases. As a consequence, the chlorinators were able to operate continuously for longer time with high efficiency. The plant can also produce higher quantity of qualified water to customers by monitoring the final water treatment process via Profit Cost (PC). The proposed 17 steps for OEE, NEE and PC evaluations are shown in this paper might be a good approach for other water treatment plant to get higher chlorinator effectiveness and lower water loss. [ABSTRACT FROM AUTHOR]

The modern manufacturing shop floor contains a variety of different types of machining equipment, each supporting different proprietary interfaces and communication protocols. This diversity has made it extremely challenging for shop managers to monitor and maintain their machines. Fortunately, the emerging MTConnect standard makes it possible for a monitoring system to accurately and consistently collect data from any MTConnect compatible machine, regardless of its brand or origin. This paper introduces a web-based machine monitoring system that provides data collection, analysis, and machine event notification for MTConnect compatible machines. This solution provides shop managers with the information needed to improve process efficiency on the shop floor, and increase overall equipment effectiveness (OEE). [ABSTRACT FROM AUTHOR]

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Industry is driven by efficiency, only this makes it possible to assert competitive advantage in the global market. Many companies use Overall Equipment Effectiveness (OEE) as a Key Performance Indicator (KPI). Currently the International Organization for Standardization (ISO) is working on standardized definitions of KPIs for Manufacturing Execution Systems (MES), based on VDMA 66412. The aim of this paper is to present a service oriented approach to OEE calculation based on ISO/DIS 22400-2 for CNC machines deployed in individual production using OPC Unified Architecture (OPC UA) as an information modelling and data transport technology. In contrast to conventional procedures for OEE calculation, where a huge amount of data is collected from shop floor level and analyzed at the supervisory level, we suggest that Key Performance Indicators are calculated as close as possible to the data sources. [ABSTRACT FROM AUTHOR]

Abstract: To compete in global market, no organization will tolerate losses. Overall Equipment Effectiveness (OEE) is such a performance measure metric which will indicate performance rate with very simple calculations. It considers all important measures of productivity. Implicitly it indicates amount of losses each parameter contributes to reduce productivity. By applying quality improvement tool such as failure Mode and Effect Analysis (FMEA) root cause of any OEE measure can be found out. It will help to improve OEE and correspondingly productivity.In this paper an attempt has been made to establish a relationship between OEE and FMEA. All the parameters of OEE (i.e. Availability, Performance Rate and Quality Rate) are evaluated with respective to FMEA (i.e. severity, occurrence and Detection). Total 32 hypothesis are considered to establish relation between OEE and FMEA. A case study conducted in one of reputed process industry gives very significant insight for OEE improvement. Power of Excel tool is explored in this paper. [Copyright &y& Elsevier]