Overall Equipment Effectiveness: Systematic Literature Review and Overview of Different Approaches

Overall equipment effectiveness (OEE) is a key performance indicator used to measure equipment productivity. The purpose of this study is to review and analyze the evolution of OEE, present modifications made over the original model and identify future development areas. This paper presents a systematic literature review; a structured and transparent study is performed by establishing procedures and criteria that must be followed for selecting relevant evidences and addressing research questions effectively. In a general search, 862 articles were obtained; after eliminating duplicates and applying certain inclusion and exclusion criteria, 186 articles were used for this review. This research presents three principal results: (1) The academic interest in this topic has increased over the last five years and the keywords have evolved from being related to maintenance and production, to being related to lean manufacturing and optimization; (2) A list of authors who have developed models based on OEE has been created; and (3) OEE is an emerging topic in areas such as logistics and services. To the best of our knowledge, no comparable review has been published recently. This research serves as a basis for future relevant studies

INSURANCE PERFORMANCE EVALUATION USING BSC-AHP COMBINED TECHNIQUE

Abstract. Insurance companies are expected to show successful performance in achieving their goals. The extent to which awareness of this organizational performance has been successful in achieving goals and where the position of organization is situated in the modern complex and dynamic context have taken on special importance to managers and organizations. Organization survival and activity are determined by competition ability and adoption of the most suitable policy for environmental changes. One of the most effective practices used by organizations is the use of performance evaluation in order to determine weaknesses and strengths of organizations and fix them and enhance their strengths. Performance management and evaluation play a prominent role in determining and implementingstrategies, as well as contributing to organizations’ competition power. In this regard, possessing a model for evaluating organization’s strategic performance seems essential. One of the techniques is the balanced scorecard which was introduced to evaluate organizations’ performance for the first time and is still recognized as a method of strategic planning which can be applicable. The balanced scorecard is a managerial concept which helps managers at all levels controls their key activities. In this research, we aim to assess the performance of various representatives of Kosar Insurance Co. in Qazvin using a combined approach, the balanced scorecard (BSC) and analytical hierarchy process (AHP), and prioritize them and explore their strengths and weaknesses.Keywords: performance evaluation, balanced scorecard, analytical hierarchy process, Qazvin Kosar Insuranc

PREDVIĐANJE KLJUČNIH PARAMETARA KVALITETE KOKSNOGA UGLJENA U STVARNOME VREMENU POMOĆU NEURONSKIH MREŽA I UMJETNE INTELIGENCIJE

High quality coke is a key raw material for the metallurgical industry. The characteristics of the coal have a significant influence on the parameters of the coke produced and, consequently, on the valuation of coal deposits and the economic assessment of mining projects. Predicting the quality of coking coal allows for the optimisation of production processes, including the planning and management of operations and the early detection of quality problems. In this study, using the principles of a smart mine, it is proposed to determine the quality of coal based on the combination of mining and geological conditions of mineral deposits and its quality indicators. Possible interrelationships between the quality of the coal in the deposit and the characteristics of the final product have been identified. A neural network is used to determine the priority of individual indicators that have a significant impact on the quality of coking coal. An important part of the research is its practical implementation in the conditions of the Jastrzębska Spółka Węglowa SA. Qualitative and quantitative parameters of coking coals were obtained for each mine of the region by the method of sampling and statistical processing of data such as: degree of metamorphism, thickness, deviation of volatile substances, presence of phosphorus, ash content, etc. For their evaluation, the Group Method of Data Handling was used to compare the factors of quality indicators depending on the priority of influence on the final characteristics of the coking coal. Based on the results obtained, it is shown that not all coal quality indicators have a significant impact on the quality of the final product. The study shows that it is possible to predict the main indicators (CRI – Coke Reactivity Index, CSR – Coke Strength after Reaction) of coke quality using neural networks based on a larger number of coal quality parameters and to eliminate parameters that have virtually no influence on the value of the final product. This method can also be used to improve the results of economic valuation of a deposit and to better plan exploration and mining operations.Koks visoke kvalitete ključna je sirovina u metalurškoj industriji. Svojstva ugljena imaju velik utjecaj na kvalitetu proizvedenoga koksa, a time i na vrednovanje ležišta ugljena i ekonomsku ocjenu rudarskih projekata. Predviđanje kvalitete ugljena za koksiranje omogućuje optimizaciju proizvodnih procesa uključujući planiranje i upravljanje procesima te rano otkrivanje problematične kvalitete. U ovoj studiji korištenjem načela pametnoga rudnika predlaže se određivanje kvalitete ugljena na temelju kombinacije rudarsko-geoloških uvjeta ležišta mineralnih sirovina i njegovih pokazatelja kakvoće. Utvrđeni su mogući međuodnosi između kvalitete ugljena u ležištu i svojstava konačnoga proizvoda. Neuronskom mrežom utvrđuje se prioritet pojedinih pokazatelja koji imaju znatan utjecaj na kvalitetu koksnoga ugljena. Važan je dio istraživanja njegova praktična provedba u kompaniji Jastrzębska Spółka Węglowa SA. Metodom uzorkovanja i statističkom obradom podataka dobiveni su kvalitativni i kvantitativni parametri koksnoga ugljena za svaki rudnik kao što su: stupanj metamorfizma, debljina, odstupanje hlapljivih tvari, prisutnost fosfora, sadržaj pepela itd. Pomoću grupne metode obrade podataka uspoređeni su pokazatelji kvalitete ovisno o prioritetu utjecaja na konačna svojstva ugljena za koksiranje. Na temelju dobivenih rezultata pokazalo se da svi pokazatelji kakvoće ugljena nemaju znatan utjecaj na kvalitetu konačnoga proizvoda. Studija pokazuje da je moguće predvidjeti glavne pokazatelje (CRI – indeks reaktivnosti koksa, CSR – čvrstoću koksa poslije reakcije s CO2) kvalitete koksa korištenjem neuronskih mreža na temelju većega broja parametara kvalitete ugljena i eliminirati parametre koji nemaju praktički nikakav utjecaj. na vrijednost konačnoga proizvoda. Ova se metoda također može koristiti za poboljšanje rezultata ekonomskoga vrednovanja ležišta i za bolje planiranje istražnih i rudarskih radova

Evaluating the effects of coal seam gas development on farms in the Surat Basin, Queensland

Previous studies have explored the contentious coexistence of agriculture and coal seam gas (CSG) development, but little research has focused on the implications of the production and profitability of individual farm enterprises and the strategies that could be implemented alongside the financial opportunities arising from coexistence. This thesis aims to address these knowledge gaps by providing insights and indicative scenarios of the potential synergy between farming and CSG operations in the Surat Basin. It is composed of three interdependent studies, which highlight the key features of the overlapping relationship of both sectors in Queensland, Australia. Study One characterises the biophysical characteristics of the agricultural areas with tenements (leased by gas companies) in the Surat Basin. These areas are classified, through fuzzy logic, according to their current land use (generally as cropping or grazing) and their inherent potential for production intensification. The study identifies these areas based on their productive value. The spatial map (using ArcGIS) is an important tool for landholders to devise management strategies to improve their farm, given the prospect of an additional cash stream from compensation. Study Two undertakes a case study analysis of some of the typical farming systems currently undergoing CSG development. Data on the spatial extent of CSG infrastructure is combined with long-term simulations of production and cash flow to estimate the possible financial losses incurred from CSG footprint. The results of the study show that both an increase in cost and a reduction in income are less than 10 percent on a farm paddock basis. Increased costs due to decreased machinery efficiency (also affected by the design of well spacing) may constitute a significant impact, which is not considered by gas companies when compensating landholders. These findings highlight important factors for farmers to consider when negotiating agreements with CSG companies. Lastly, Study Three focuses on the financial opportunity that coexistence between agriculture and CSG presents. This study demonstrates the benefits of the compensation arrangement, for which there is a gap in literature. The results of the study show that the overall financial performance of the farm enterprise improves with the advent of compensation as cash flow becomes steadily positive. The study concludes that the indicative amount of compensation is enough to restore the profitability of a hypothetical farm paddock to its baseline production prior to CSG development, and that farm investment is the most profitable option for both dryland and irrigated farming systems. This is a novel research, which provides information and documentation of the coexistence of agriculture and CSG development. The thesis serves as an important input for negotiations and contract agreements. It highlights key areas and strategies that can minimisecosts and maximise benefits of coexistence. Further research is recommended on areas of coexistence related to: (a) modelling of other important farming systems within CSG development areas, such as grazing, and (b) valuing intangible impacts

Design and Implementation of Coal Mine Physiological Parameters Monitoring Protocol

Modernization in the industries also concerns with the safety of workers especially for underground mining?s. This paper mainly deals with surveillance and safety measures for mine workers, which is most essential in underground mining areas. Here, a concept of wireless sensors network is used to monitor the environment parameters of underground mine area and all sensed parameters are sent to host computer. Arduino Microcontroller is a heart of a system used to build a fully automated measuring system with reliability, high accuracy and smooth control. Upon detecting critical conditions, alert system starts and the same information is transmitted to remote location by ZigBee Communication. The observed changes in the parameters will also be displayed on the host computer at base station which makes it easier for the underground control center to monitor and to take necessary immediate action to avoid damages

Studies on Risk and Occupational Health Hazards in Industrial Context: Some Case Research

This work articulates few case empirical studies on some aspects of risk management and occupational health hazards in the context of Indian Industries. Empirical research is research using empirical evidence. It is a way of gaining knowledge by means of direct and indirect observation or experience. The study focuses on five important domains investigating (i) the interrelationships among critical risk factors associated with software engineering project, (ii) risk management for IT outsourcing, (iii) risk management in metropolitan construction project, (iv) health hazard risk management, and (v) appropriate safety measure system selection for improving workers’ safety in an underground coal mining industry. In this research, an ISM approach has been applied to understand the significant interrelationships among the twenty three identified risk factors associated with the software engineering projects. In relation to IT outsourcing project, a hierarchical risk-breakdown structure has been proposed comprising sixty eight risk influencing factors under eleven risk dimensions. A case study has been conducted in a famous IT sector located at the eastern part of India. An improved fuzzy based decision making approach has been proposed for assessing overall IT outsourcing project risks. The degree of risk of identified risk factors have been shown in crisp values rather than the fuzzy numbers. A logical risk categorization framework has been proposed to categorize the risk factors into different risk levels. A unique action requirement plan has been suggested for effectively controlling the risks towards IT outsourcing project success. In the later part, total twenty one occupational health hazards have been identified and assessed their risk extent based on the exposure assessment procedure. Consequently, a constructive control measure plan has been suggested for different health hazards in view of their risk extent level. A novel risk-based decision making framework has been proposed for selecting the appropriate safety measure system in an underground coal mining industry. In addition to this, a case study has been conducted using twenty potential risk factors associated with five risk dimensions for assessing metropolitan construction project risks. Decision-makers’ risk bearing attitude has also been considered in this study. This study also explores the concept of risk matrix for categorizing the risk factors in different risk levels which would provide guidelines towards controlling risks for enhancing the overall project performance. Risk analysis models delignated herein have been case studied in relation to Indian industries. However, the model or hierarchy of various risk dimensions, risk sources; and classification of health hazards can be applicable to appropriate industries all over the globe. Some alteration may incur depending on the geographic situation of coal mining industry in analyzing occupational health hazards and associated risks. The framework for analyzing risks and occupational health hazards based on fuzzy based decision making approach can be applied in industrial context of different countries. Apart from the case studies mentioned above, the work also proposes a risk based decision support framework for selection of safety measure system for underground coal mines. In this case, occupational risks and alternative safety measure systems have been identified through literature survey. This part is a purely a theoretical formulation followed by analysis of assumed data which has not been case studied in reality. The novelty of the proposed framework is to analyze various risk dimensions in software engineering projects, IT Outsourcing, construction projects; also occupational health hazards in underground coal mining industry in a fuzzy based decision making framework. Instead of exploring historical data, survey report of the company; an experienced decision making group has been appointed to provide subjective judgement in regards of likelihood of occurrence and impact of various risks; consequence of exposure, period of exposure, and probability of exposure of various health hazards. Subjective decision making data have been transformed into appropriate fuzzy number sets to quantify overall risks extent. Thus, the proposed framework provides a platform to quantify extent of risk in industrial context

Assessing industrial ecosystem vulnerability in the coal mining area under economic fluctuations

In the context of the depth adjustment of the global economy and wild fluctuations in energy prices, the vulnerability issue of the coal mining industrial ecosystem (CMIES) has seriously affected the sustainable development of the regional economy. Comparisons of CMIES health status at a regional level are worthy of being conducted. This not only contributes to understanding a particular coal mining area's situation in regards to CMIES vulnerability, but also helps to discover a meaningful benchmark to learn the experiences in terms of action programmes formulation. In this study, based on the analysis of the vulnerability response mechanism of CMIES to economic fluctuations, an initial indicator system for vulnerability assessment of CMIES was constructed. Ultimately, 14 vulnerability-evaluating indicators and their weights were obtained using rough set attribute reduction. Based on a composite CMIES Vulnerability Index (CVI), the Rough Set-Technique for Order Preference by Similarity to Ideal Solution-Rank-sum Ratio (RS-TOPSIS-RSR) methodology is proposed to conduct the CMIES vulnerability assessment process from an overall perspective. Using this methodology, 33 coal mining areas in China are ranked as well as grouped into three specific groups based on the CVI score. The results demonstrate the feasibility of the proposed method as a valuable tool for decision making and performance evaluation with multiple alternatives and criteria

Open innovation in the power & energy sector: Bringing together government policies, companies’ interests, and academic essence

The Power and Energy (P&E) sector needs to respond to several challenges fostering investments in research and development. According to the Open Innovation (OI) paradigm, key stakeholders like utilities, vendors, laboratories, universities etc. should take advantage of external knowledge to improve their innovation performance. Several studies have demonstrated that firms adopting the OI paradigm are more likely to innovate. Despite the interest of P&E firms in enhancing their innovation capabilities, surprisingly few articles (usually case studies) described the implementation of the OI paradigm in P&E firms. This article fills the gap by identifying the key drivers that encourage a firm in the P&E sector to embrace the OI paradigm. The authors adopt a hybrid research approach collecting evidence from the literature and through a multiple case-study analysis involving seven British firms and universities operating in the P&E industry. As the drivers of OI have mutual influence, this article describes them with a fuzzy cognitive map. Finally, the authors identify appropriated policies to enhance the OI adoption and, consequently, the sustainability of innovation in the P&E sector. A salient research agenda closes the paper

Impacts of FDI Renewable Energy Technology Spillover on China's Energy Industry Performance

Environmental friendly renewable energy plays an indispensable role in energy industry development. Foreign direct investment (FDI) in advanced renewable energy technology spillover is promising to improve technological capability and promote China’s energy industry performance growth. In this paper, the impacts of FDI renewable energy technology spillover on China’s energy industry performance are analyzed based on theoretical and empirical studies. Firstly, three hypotheses are proposed to illustrate the relationships between FDI renewable energy technology spillover and three energy industry performances including economic, environmental, and innovative performances. To verify the hypotheses, techniques including factor analysis and data envelopment analysis (DEA) are employed to quantify the FDI renewable energy technology spillover and the energy industry performance of China, respectively. Furthermore, a panel data regression model is proposed to measure the impacts of FDI renewable energy technology spillover on China’s energy industry performance. Finally, energy industries of 30 different provinces in China based on the yearbook data from 2005 to 2011 are comparatively analyzed for evaluating the impacts through the empirical research. The results demonstrate that FDI renewable energy technology spillover has positive impacts on China’s energy industry performance. It can also be found that the technology spillover effects are more obvious in economic and technological developed regions. Finally, four suggestions are provided to enhance energy industry performance and promote renewable energy technology spillover in China