Search results for: operational approach

Authors: Chukwumeka Daniel Ezeliora

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The Nigerian manufacturing sector plays a pivotal role in the country's economic growth and development. However, it faces numerous challenges, including operational inefficiencies and inherent risks that hinder its sustainable growth. This research aims to address these challenges by exploring the integration of Lean and Six Sigma methodologies into the manufacturing processes, ultimately enhancing operational effectiveness and risk mitigation. The core of this research involves the development of a sustainable Lean Six Sigma framework tailored to the specific needs and challenges of Nigeria's manufacturing environment. This framework aims to streamline processes, reduce waste, improve product quality, and enhance overall operational efficiency. It incorporates principles of sustainability to ensure that the proposed methodologies align with environmental and social responsibility goals. To validate the effectiveness of the integrated Lean Six Sigma approach, case studies and real-world applications within select manufacturing companies in Nigeria will be conducted. Data were collected to measure the impact of the integration on key performance indicators, such as production efficiency, defect reduction, and risk mitigation. The findings from this research provide valuable insights and practical recommendations for selected manufacturing companies in South East Nigeria. By adopting sustainable Lean Six Sigma methodologies, these organizations can optimize their operations, reduce operational risks, improve product quality, and enhance their competitiveness in the global market. In conclusion, this research aims to bridge the gap between theory and practice by developing a comprehensive framework for the integration of Lean and Six Sigma methodologies in Nigeria's manufacturing sector. This integration is envisioned to contribute significantly to the sector's sustainable growth, improved operational efficiency, and effective risk mitigation strategies, ultimately benefiting the Nigerian economy as a whole.

Keywords: lean six sigma, manufacturing, risk mitigation, sustainability, operational efficiency

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Authors: Zehra Sultan

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The study is based on the task-based language teaching approach which is found to be very effective in the EFL/ESL classroom. This approach engages learners to acquire the usage of authentic language skills by interacting with the real world through sequence of pedagogical tasks. The use of technology enhances the effectiveness of this approach. This study throws light on the historical background of TBLT and its efficacy in the EFL/ESL classroom. In addition, this study precisely talks about the implementation of this approach in the General Foundation Programme of Muscat College, Oman. It furnishes the list of the pedagogical tasks embedded in the language curriculum of General Foundation Programme (GFP) which are skillfully allied to the College Graduate Attributes. Moreover, the study also discusses the challenges pertaining to this approach from the point of view of teachers, students, and its classroom application. Additionally, the operational success of this methodology is gauged through formative assessments of the GFP, which is apparent in the students’ progress.

Keywords: task-based language teaching, authentic language, communicative approach, real world activities, ESL/EFL activities

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Authors: Dimitrios Kafetzopoulos

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Nowadays, companies are more concerned with adopting their own strategies for increased efficiency and sustainability. Dynamic environments are fertile fields for developing operational changes. For this purpose, organizations need to implement an advanced management philosophy that boosts changes to companies’ operation. Changes refer to new applications of knowledge, ideas, methods, and skills that can generate unique capabilities and leverage an organization’s competitiveness. So, in order to survive and compete in the global and niche markets, companies should incorporate the adoption of operational changes into their strategy with regard to their products and their processes. Creating the appropriate culture for changes in terms of products and processes helps companies to gain a sustainable competitive advantage in the market. Thus, the purpose of this study is to investigate the role of both incremental and radical changes into operations of a company, taking into consideration not only product changes but also process changes, and continues by measuring the impact of these two types of changes on business efficiency and sustainability of Greek manufacturing companies. The above discussion leads to the following hypotheses: H1: Radical operational changes have a positive impact on firm efficiency. H2: Incremental operational changes have a positive impact on firm efficiency. H3: Radical operational changes have a positive impact on firm sustainability. H4: Incremental operational changes have a positive impact on firm sustainability. In order to achieve the objectives of the present study, a research study was carried out in Greek manufacturing firms. A total of 380 valid questionnaires were received while a seven-point Likert scale was used to measure all the questionnaire items of the constructs (radical changes, incremental changes, efficiency and sustainability). The constructs of radical and incremental operational changes, each one as one variable, has been subdivided into product and process changes. Non-response bias, common method variance, multicollinearity, multivariate normal distribution and outliers have been checked. Moreover, the unidimensionality, reliability and validity of the latent factors were assessed. Exploratory Factor Analysis and Confirmatory Factor Analysis were applied to check the factorial structure of the constructs and the factor loadings of the items. In order to test the research hypotheses, the SEM technique was applied (maximum likelihood method). The goodness of fit of the basic structural model indicates an acceptable fit of the proposed model. According to the present study findings, radical operational changes and incremental operational changes significantly influence both efficiency and sustainability of Greek manufacturing firms. However, it is in the dimension of radical operational changes, meaning those in process and product, that the most significant contributors to firm efficiency are to be found, while its influence on sustainability is low albeit statistically significant. On the contrary, incremental operational changes influence sustainability more than firms’ efficiency. From the above, it is apparent that the embodiment of the concept of the changes into the products and processes operational practices of a firm has direct and positive consequences for what it achieves from efficiency and sustainability perspective.

Keywords: incremental operational changes, radical operational changes, efficiency, sustainability

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Authors: Mahsa Karimpour, Martin Belusko, Ke Xing, Frank Bruno

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Traditionally the embodied energy of design choices which reduce operational energy were assumed to have a negligible impact on the life cycle energy of buildings. However with new buildings having considerably lower operational energy, the significance of embodied energy increases. A life cycle assessment of a population of house designs was conducted in a mild and mixed climate zone. It was determined not only that embodied energy dominates life cycle energy, but that the impact on embodied of design choices was of equal significance to the impact on operational energy.

Keywords: building life cycle energy, embodied energy, energy design measures, low energy buildings

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Authors: Muogbo Chukwudi Peter, Gbabo Agidi

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Influence of different turmeric rhizome sizes and machine operational speed on the field capacity and efficiency of a developed prototype tractor-drawn turmeric planter was studied. This was done with a view to ascertaining how the field capacity and field efficiency were affected by the turmeric rhizome lengths and tractor operational speed. The turmeric rhizome planter consists of trapezoidal hopper, grooved cylindrical metering devise, rectangular frame, ground wheels made of mild steel, furrow opener, chain/sprocket drive system, three linkage point seed delivery tube and press wheel. The experiment was randomized in a factorial design of three levels of rhizome lengths (30, 45 and 60 mm) and operational speeds of 8, 10, and 12 kmh-1. About 3 kg cleaned turmeric rhizomes were introduced into each hopper of the planter and were planted 30 m2 of experimental plot. During the field evaluation of the planter, the effective field capacity, field efficiency, missing index, multiple index and percentage rhizome bruise were evaluated. 30.08% was recorded for maximum percentage bruise on the rhizome. The mean effective field capacity ranged between 0.63 – 0.96hah-1 at operational speeds of 8 and 12kmh-1 respectively and 45 mm rhizome length. The result also shows that the mean efficiency was obtained to be 65.8%. The percentage rhizome bruise decreases with increase in operational speed. The highest and lowest percentage turmeric rhizome miss index of 35% were recorded for turmeric rhizome length of 30 mm at a speed of 10 kmhr-1 and 8 kmhr-1, respectively. The potential implications of the experimental result is to determine the optimal machine process conditions for higher field capacity and gross reduction in mechanical injury (bruise) of planted turmeric rhizomes.

Keywords: rhizome sizes, operational speed, field capacity. field efficiency, turmeric rhizome, planter

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Authors: Ahmed Kadry, Gwyn Dodd

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There has been a growing call globally for police forces to embed evidence-based policing research methods into police interventions in order to better understand and evaluate their impact. This research study highlights the success and challenges that police forces may encounter when trying to embed evidence-based research methods within their organisation. 10 in-depth qualitative interviews were conducted with police officers and staff at Greater Manchester Police (GMP) who were tasked with integrating evidence-based research methods into their operational interventions. The findings of the study indicate that with adequate resources and individual expertise, evidence-based research methods can be applied to operational work, including the testing of initiatives with strict controls in order to fully evaluate the impact of an intervention. However, the findings also indicate that this may only be possible where an operational intervention is heavily resourced with police officers and staff who have a strong understanding of evidence-based policing research methods, attained for example through their own graduate studies. In addition, the findings reveal that ample planning time was needed to trial operational interventions that would require strict parameters for what would be tested and how it would be evaluated. In contrast, interviewees underscored that operational interventions with the need for a speedy implementation were less likely to have evidence-based research methods applied. The study contributes to the wider literature on evidence-based policing by providing considerations for police forces globally wishing to apply evidence-based research methods to more of their operational work in order to understand their impact. The study also provides considerations for academics who work closely with police forces in assisting them to embed evidence-based policing. This includes how academics can provide their expertise to police decision makers wanting to underpin their work through evidence-based research methods, such as providing guidance on how to evaluate the impact of their work with varying research methods that they may otherwise be unaware of.  

Keywords: evidence based policing, evidence-based practice, operational policing, organisational change

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Authors: Mehmet Savsar, Majid Aldaihani

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Flexible Manufacturing Systems (FMS) are used to produce a variety of parts on the same equipment. Therefore, their utilization is higher than traditional machining systems. Higher utilization, on the other hand, results in more frequent equipment failures and additional need for maintenance. Therefore, it is necessary to carefully analyze operational characteristics and productivity of FMS or Flexible Manufacturing Cells (FMC), which are smaller configuration of FMS, before installation or during their operation. Appropriate models should be developed to determine production rates based on operational conditions, including equipment reliability, availability, and repair capacity. In this paper, a stochastic model is developed for an automated FMC system, which consists of two machines served by two robots and a single repairman. The model is used to determine system productivity and equipment utilization under different operational conditions, including random machine failures, random repairs, and limited repair capacity. The results are compared to previous study results for FMC system with sufficient repair capacity assigned to each machine. The results show that the model will be useful for design engineers and operational managers to analyze performance of manufacturing systems at the design or operational stages.

Keywords: flexible manufacturing, FMS, FMC, stochastic modeling, production rate, reliability, availability

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Authors: Gerhard Grebe, Johan Marx

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The aim of the study is to assess the state of operational risk management and the adoption of an appropriate risk culture in Ghanaian banks. The Bank of Ghana (BoG) joined the Basel Consultative Group (BCG) of the Basel Committee on Bank Supervision (BCBS) in 2021 and is proceeding with the implementation of the Basel III international regulatory framework for banks. The BoG’s Directive about risk management encourages, inter alia, the creation of an appropriate risk culture by Ghanaian banks. However, it is not evident how the risk management staff of Ghanaian banks experience the risk culture and the implementation of operational risk management in the banks where they are employed. Ghana is a developing economy, and it is addressing challenges with its organisational culture. According to Transparency International, successive Ghanaian governments claim to be fighting corruption, but little success has been achieved so far. This points to a possible lack of accountability, transparency, and integrity in the environment in which Ghanaian banks operate and which could influence their risk culture negatively. Purposive sampling was used for the survey, and the questionnaire was completed byGhanaian bank personnel who specializesin operational risk management, risk governance, and compliance, bank supervision, risk analyses, as well as the implementation of the operational risk management requirements of the Basel regulatory frameworks. The respondents indicated that they are fostering a risk culture and implementing monitoring and reporting procedures; the three lines of defence (3LOD); compliance; internal auditing; disclosure of operational risk information; and receiving guidance from the bank supervisor in an attempt to improve their operational risk management practices. However, the respondents reported the following challenges with staff members who are not inside the risk management departments(in order of priority), namelydemonstrating a risk culture, training and development; communication; reporting and disclosure; roles and responsibilities; performance appraisal; and technological and environmental barriers. Recommendations to address these challenges are provided

Keywords: ghana, operational risk, risk culture, risk management

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Authors: Zexiao Zheng, Irene M. C. Lo

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Organic pollutants, ammonia, and bacteria are major contaminants in sewage, which may adversely impact ecosystems without proper treatment. Conventional wastewater treatment plants (WWTPs) are operated to remove these contaminants from sewage but suffer from high carbon emissions and are powerless to remove emerging organic pollutants (EOPs). Herein, we have developed a low operational carbon emissions multifunctional photoelectrochemical (PEC) system for saline sewage treatment to simultaneously remove organic compounds, ammonia, and bacteria, coupled with H2 evolution. A reduced BiVO4 (r-BiVO4) with improved PEC properties due to the construction of oxygen vacancies and V4+ species was developed for the multifunctional PEC system. The PEC/r-BiVO4 process could treat saline sewage to meet local WWTPs’ discharge standard in 40 minutes at 2.0 V vs. Ag/AgCl and completely degrade carbamazepine (one of the EOPs), coupled with significant evolution of H2. A remarkable reduction in operational carbon emissions was achieved by the PEC/r-BiVO4 process compared with large-scale WWTPs, attributed to the restrained direct carbon emissions from the generation of greenhouse gases. Mechanistic investigation revealed that the PEC system could activate chloride ions in sewage to generate reactive chlorine species and facilitate •OH production, promoting contaminants removal. The PEC system exhibited operational feasibility at different pH and total suspended solids concentrations and has outstanding reusability and stability, confirming its promising practical potential. The study combined the simultaneous removal of three major contaminants from saline sewage and H2 evolution in a single PEC process, demonstrating a viable approach to supplementing and extending the existing wastewater treatment technologies. The study generated profound insights into the in-situ activation of existing chloride ions in sewage for contaminants removal and offered fundamental theories for applying the PEC system in sewage remediation with low operational carbon emissions. The developed PEC system can fit well with the future needs of wastewater treatment because of the following features: (i) low operational carbon emissions, benefiting the carbon neutrality process; (ii) higher quality of the effluent due to the elimination of EOPs; (iii) chemical-free in the operation of sewage treatment; (iv) easy reuse and recycling without secondary pollution.

Keywords: contaminants removal, H2 evolution, multifunctional PEC system, operational carbon emissions, saline sewage treatment, r-BiVO4 photoanodes

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Authors: Hsin-Yi Huang, Ming-Sheng Liu, Jiun-Yan Shiau

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Planning the order picking lists of warehouses to achieve when the costs associated with logistics on the operational performance is a significant challenge. In e-commerce era, this task is especially important productive processes are high. Nowadays, many order planning techniques employ supervised machine learning algorithms. However, the definition of which features should be processed by such algorithms is not a simple task, being crucial to the proposed technique’s success. Against this background, we consider whether unsupervised algorithms can enhance the planning of order-picking lists. A Zone2 picking approach, which is based on using clustering algorithms twice, is developed. A simplified example is given to demonstrate the merit of our approach.

Keywords: order picking, warehouse, clustering, unsupervised learning

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Peter Chemweno

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The fast-changing business and operational environment are forcing organizations to adopt asset performance management strategies, not only to reduce costs but also maintain operational and production policies while addressing demand. To attain optimal asset performance management, a framework that ensures a continuous and systematic approach to analyzing an organization’s current maturity level and expected improvement regarding asset maintenance processes, strategies, technologies, capabilities, and systems is essential. Moreover, this framework while addressing maintenance-intensive organizations should consider the diverse business, operational and technical context (often dynamic) an organization is in and realistically prescribe or relate to the appropriate tools and systems the organization can potentially employ in the respective level, to improve and attain their maturity goals. This paper proposes an asset maintenance maturity model to assess the current capabilities, strength and weaknesses of maintenance processes an organization is using and analyze gaps for improvement via structuring set levels of achievement. At the epicentre of the proposed framework is the utilization of maintenance objective selected by an organization for various maintenance optimization programs. The framework adapts the Capability Maturity Model of assessing the maintenance process maturity levels in the organization.

Keywords: asset maintenance, maturity models, maintenance objectives, optimization

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Authors: Raúl González Muñoz, Essam Shehab, Martin Weinitzke, Chris Fowler, Paul Baguley

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Software applications have become crucial to the aerospace industry, providing a wide range of functionalities and capabilities used during the design, manufacturing and support of aircraft. However, as this criticality increases, so too does the risk for business operations when facing a software failure. Hence, there is a need for new methodologies to be developed to support aerospace companies in effectively managing their software portfolios, avoiding the hazards of business disruption and additional costs. This paper aims to provide a definition of operational software maturity, and how this can be used to assess software operational behaviour, as well as a view on the different aspects that drive software maturity within the aerospace industry. The key research question addressed is, how can operational software maturity monitoring assist the aerospace industry in effectively managing large software portfolios? This question has been addressed by conducting an in depth review of current literature, by working closely with aerospace professionals and by running an industry case study within a major aircraft manufacturer. The results are a software maturity model composed of a set of drivers and a prototype tool used for the testing and validation of the research findings. By utilising these methodologies to assess the operational maturity of software applications in aerospace, benefits in maintenance activities and operations disruption avoidance have been observed, supporting business cases for system improvement.

Keywords: aerospace, software lifecycle, software maintenance, software maturity

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Authors: Sachin Kumar

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Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy.

Keywords: fractional PDE, fuzzy valued function, diffusion equation, Legendre polynomial, spectral method

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Authors: Manpreet Singh, V. P. Agrawal, Gurmanjot Singh Bhatti

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From the last decades, there is a significant technological advancement in the field of robotics, and a number of modular self-reconfigurable robots were introduced that can help in space exploration, bucket to stuff, search, and rescue operation during earthquake, etc. As there are numbers of self-reconfigurable robots, choosing the optimum one is always a concern for robot user since there is an increase in available features, facilities, complexity, etc. The objective of this research work is to present a multiple attribute decision making based methodology for coding, evaluation, comparison ranking and selection of modular self-reconfigurable robots using a technique for order preferences by similarity to ideal solution approach. However, 86 attributes that affect the structure and performance are identified. A database for modular self-reconfigurable robot on the basis of different pertinent attribute is generated. This database is very useful for the user, for selecting a robot that suits their operational needs. Two visual methods namely linear graph and spider chart are proposed for ranking of modular self-reconfigurable robots. Using five robots (Atron, Smores, Polybot, M-Tran 3, Superbot), an example is illustrated, and raking of the robots is successfully done, which shows that Smores is the best robot for the operational need illustrated, and this methodology is found to be very effective and simple to use.

Keywords: self-reconfigurable robots, MADM, TOPSIS, morphogenesis, scalability

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Authors: Da-Ming Huang, Ya-Ting Tsai, Shyh-Hau Wang

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Ultrasound signals backscattered from the soft tissues are mainly depending on the size, density, distribution, and other elastic properties of scatterers in the interrogated sample volume. The quantitative analysis of ultrasonic backscattering is frequently implemented using the statistical approach due to that of backscattering signals tends to be with the nature of the random variable. Thus, the statistical analysis, such as Nakagami statistics, has been applied to characterize the density and distribution of scatterers of a sample. Yet, the accuracy of statistical analysis could be readily affected by the receiving signals associated with the nature of incident ultrasound wave and acoustical properties of samples. Thus, in the present study, efforts were made to explore such effects as the ultrasound operational modes and attenuation of biological tissue on the estimation of corresponding Nakagami statistical parameter (m parameter). In vitro measurements were performed from healthy and pathological fibrosis porcine livers using different single-element ultrasound transducers and duty cycles of incident tone burst ranging respectively from 3.5 to 7.5 MHz and 10 to 50%. Results demonstrated that the estimated m parameter tends to be sensitively affected by the use of ultrasound operational modes as well as the tissue attenuation. The healthy and pathological tissues may be characterized quantitatively by m parameter under fixed measurement conditions and proper calibration.

Keywords: ultrasound backscattering, statistical analysis, operational mode, attenuation

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Authors: Linet Melisa Daubanes, Nhleko Monique Chiloane

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The shovel-truck system is the most prevalent material handling system used in surface mining operations. Material handling entails the loading and hauling of material from production areas to dumping areas. The material handling process has operational delays that have a negative impact on the productivity of the load and haul fleet. Factors that may contribute to operational delays include shovel-truck mismatch, haul routes, machine breakdowns, extreme weather conditions, etc. The aim of this paper is to investigate factors that contribute to operational delays affecting the productivity of the load and haul fleet at the mine. Productivity is the measure of the effectiveness of producing products from a given quantity of units, the ratio of output to inputs. Productivity can be improved by producing more outputs with the same or fewer units and/or introducing better working methods etc. Several key performance indicators (KPI) for the evaluation of productivity will be discussed in this study. These KPIs include but are not limited to hauling conditions, bucket fill factor, cycle time, and utilization. The research methodology of this study is a combination of on-site time studies and observations. Productivity can be optimized by managing the factors that affect the operational performance of the haulage fleet.

Keywords: cycle time, fleet performance, load and haul, surface mining

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Authors: K. -H. Yang

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Supplier selection problem is one of the important issues of supply chain problems. Two categories of methodologies include qualitative and quantitative approaches which can be applied to supplier selection problems. However, due to the complexities of the problem and lacking of reliable and quantitative data, qualitative approaches are more than quantitative approaches. This study considers operational cost and supplier’s reliability factor and solves the problem by using a quantitative approach. A mixed integer programming model is the primary analytic tool. Analyses of different scenarios with variable cost and reliability structures show that the effectiveness of this approach to the supplier selection problem.

Keywords: mixed integer programming, quantitative approach, supplier’s reliability, supplier selection

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Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: Anocha Kimkong, Natnichar Kleebbuabarn

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This research work has the objective to analyze the financial status and operational performance of Suan Sunandha Rajabhat University (SSRU) in 3 fiscal years (2011-2013). The tool used is a form to record financial statements and balances of the university. The analysis is based on the calculation that regards the figures in the fiscal year of 2011 as the 100% bases to be compared with the same figures in the fiscal years of 2012 and 2013, which are multiplied by 100 and divided by the base figures. The outcomes are the percentages of each year, which can reflect the rising, stable, and falling trends. The results from the analysis reveal that SSRU’s financial status is getting better because the gross assets, debts and accumulated cash are increasing in the fiscal years of 2012 and 2013. Concerning the operational performance, the university’s incomes and expenses are rising from the fiscal year of 2011. This makes the university’s incomes grow higher than expenses.

Keywords: financial status, operational performance, Suan Sunandha Rajabhat University, balances

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Authors: Teimuraz Manjapharashvili, Ketevani Manjaparashvili

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Fuzzy logic is a modeling method for complex or ill-defined systems and is a relatively new mathematical approach. Its basis is to consider overlapping cases of parameter values and define operations to manipulate these cases. Fuzzy logic can successfully create operative automatic management or appropriate advisory systems. Fuzzy logic techniques in various operational control technologies have grown rapidly in the last few years. Fuzzy logic is used in many areas of human technological activity. In recent years, fuzzy logic has proven its great potential, especially in the automation of industrial process control, where it allows to form of a control design based on the experience of experts and the results of experiments. The engineering of chemical technological processes uses fuzzy logic in optimal management, and it is also used in process control, including the operational control of continuous cycle chemical industrial, technological processes, where special features appear due to the continuous cycle and correct management acquires special importance. This paper discusses how intelligent systems can be developed, in particular, how fuzzy logic can be used to build knowledge-based expert systems in chemical process engineering. The implemented projects reveal that the use of fuzzy logic in technological process control has already given us better solutions than standard control techniques. Fuzzy logic makes it possible to develop an advisory system for decision-making based on the historical experience of the managing operator and experienced experts. The present paper deals with operational control and management systems of continuous cycle chemical technological processes, including advisory systems. Because of the continuous cycle, many features are introduced in them compared to the operational control of other chemical technological processes. Among them, there is a greater risk of transitioning to emergency mode; the return from emergency mode to normal mode must be done very quickly due to the impossibility of stopping the technological process due to the release of defective products during this period (i.e., receiving a loss), accordingly, due to the need for high qualification of the operator managing the process, etc. For these reasons, operational control systems of continuous cycle chemical technological processes have been specifically discussed, as they are different systems. Special features of such systems in control and management were brought out, which determine the characteristics of the construction of control and management systems. To verify the findings, the development of an advisory decision-making information system for operational control of a lime kiln using fuzzy logic, based on the creation of a relevant expert-targeted knowledge base, was discussed. The control system has been implemented in a real lime production plant with a lime burn kiln, which has shown that suitable and intelligent automation improves operational management, reduces the risks of releasing defective products, and, therefore, reduces costs. The special advisory system was successfully used in the said plant both for the improvement of operational management and, if necessary, for the training of new operators due to the lack of an appropriate training institution.

Keywords: chemical process control systems, continuous cycle industrial technological processes, fuzzy logic, lime kiln

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Authors: Khosrow Maleknejad, Yaser Rostami

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In this paper, semi-orthogonal B-spline scaling functions and wavelets and their dual functions are presented to approximate the solutions of integro-differential equations.The B-spline scaling functions and wavelets, their properties and the operational matrices of derivative for this function are presented to reduce the solution of integro-differential equations to the solution of algebraic equations. Here we compute B-spline scaling functions of degree 4 and their dual, then we will show that by using them we have better approximation results for the solution of integro-differential equations in comparison with less degrees of scaling functions.

Keywords: ıntegro-differential equations, quartic B-spline wavelet, operational matrices, dual functions

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Authors: Adam Y. Sulaiman, Donal F. Cotter, Ming J. Huang, Neil J. Hewitt

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Suitable low global warming potential (GWP) refrigerants that conform to F-gas regulations are required to extend the operational envelope of high-temperature heat pumps (HTHPs) used for industrial waste heat recovery processes. The thermophysical properties and characteristics of these working fluids need to be assessed to provide a comprehensive understanding of operational effectiveness in HTHP applications. This paper presents the results of a theoretical simulation to investigate a range of low-GWP refrigerants and their suitability to supersede refrigerants HFC-245fa and HFC-365mfc. A steady-state thermodynamic model of a single-stage HTHP with an internal heat exchanger (IHX) was developed to assess system cycle characteristics at temperature ranges between 50 to 80 °C heat source and 90 to 150 °C heat sink. A practical approach to maximize the operational efficiency was examined to determine the effects of regulating minimum superheat within the process and subsequent influence on energetic and exergetic efficiencies. A comprehensive map of minimum superheat across the HTHP operating variables were used to assess specific tipping points in performance at 30 and 70 K temperature lifts. Based on initial results, the refrigerants HCFO-1233zd(E) and HFO-1336mzz(Z) were found to be closely aligned matches for refrigerants HFC-245fa and HFC-365mfc. The overall results show effective performance for HCFO-1233zd(E) occurs between 5-7 K minimum superheat, and HFO-1336mzz(Z) between 18-21 K dependant on temperature lift. This work provides a method to optimize refrigerant selection based on operational indicators to maximize overall HTHPs system performance.

Keywords: high-temperature heat pump, minimum superheat, energy & exergy efficiency, low GWP refrigerants

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Authors: Renata Konadu

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Over the last two decades, the concept of environmental management and its related issues have received increased attention in global discourse and on management research agenda due to climate change and other environmental challenges. To abate and avert these challenges, diverse environmental policies, strategies and practices have been adopted by businesses and economies as a whole. Extant literature has placed much emphasis on whether improved environmental operational performance improves firm performance. However, there is a huge gap in the literature with regards to whether the adoption of environmental management practices and policies has a direct relationship with environmental operational performance (EOP). The current paper is intended to provide a comprehensive perspective of how different aspects of environmental management can relate to firms EOP. Using a panel regression analysis of 149 large listed firms in the UK, the study found evidence of both negative and positive statistically significant link between some Environmental Policies (EP), Environmental Processes (EPR), Environmental Management Systems (EMS) and EOP. The findings suggest that in terms of relating EP, EPR and EMS to Greenhouse Gases (GHGs) emissions for instance, the latter should be viewed separately in Scopes 1, 2 and 3 as developed by GHG protocol. The results have useful implication for policy makers and managers when designing strategies and policies to reduce negative environmental impacts.

Keywords: environmental management, environmental operational performance, GHGs, large listed firms

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Authors: Mario Gianni, Federico Nardi, Federico Ferri, Filippo Cantucci, Manuel A. Ruiz Garcia, Karthik Pushparaj, Fiora Pirri

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In this paper, we describe a Mixed-Initiative Operational Model (MIOM) which directly intervenes on the state of the functionalities embedded into a robot for Urban Search&Rescue (USAR) domain applications. MIOM extends the reasoning capabilities of the vehicle, i.e. mapping, path planning, visual perception and trajectory tracking, with operator knowledge. Especially in USAR scenarios, this coupled initiative has the main advantage of enhancing the overall performance of a rescue mission. In-field experiments with rescue responders have been carried out to evaluate the effectiveness of this operational model.

Keywords: mixed-initiative planning and control, operator control interfaces for rescue robotics, situation awareness, urban search, rescue robotics

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Authors: Rims Janeliukstis, Deniss Mironovs, Andrejs Kovalovs

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Operational Modal Analysis (OMA) is widely applied as a method for Structural Health Monitoring for structural damage identification and assessment by tracking the changes of the identified modal parameters over time. Unfortunately, modal parameters also depend on such external factors as temperature and loads. Any structural condition assessment using modal parameters should be done taking into consideration those external factors, otherwise there is a high chance of false positives. A method of structural reliability assessment based on anomaly detection technique called Machalanobis Squared Distance (MSD) is proposed. It requires a set of reference conditions to learn healthy state of a structure, which all future parameters are compared to. In this study, structural modal parameters (natural frequency and mode shape), as well as ambient temperature and loads acting on the structure are used as features. Numerical tests were performed on a finite element model of a carbon fibre reinforced polymer composite beam with delamination damage at various locations and of various severities. The advantages of the demonstrated approach include relatively few computational steps, ability to distinguish between healthy and damaged conditions and discriminate between different damage severities. It is anticipated to be promising in reliability assessment of massively produced structural parts.

Keywords: operational modal analysis, reliability assessment, anomaly detection, damage, mahalanobis squared distance

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Authors: Hassan Jassim Motlak

Abstract:

A novel design technique employing CMOS Current Feedback Operational Amplifier (CFOA) is presented. The feature of consumption whivh has a very low power in designing pseudo-OTA is used to decreasing the total power consumption of the proposed CFOA. This design approach applies pseudo-OTA as input stage cascaded with buffer stage. Moreover, the DC input offset voltage and harmonic distortion (HD) of the proposed CFOA are very low values compared with the conventional CMOS CFOA due to symmetrical input stage. P-Spice simulation results using 0.18µm MIETEC CMOS process parameters using supply voltage of ±1.2V and 50μA biasing current. The P-Spice simulation shows excellent improvement of the proposed CFOA over existing CMOS CFOA. Some of these performance parameters, for example, are DC gain of 62. dB, open-loop gain-bandwidth product of 108 MHz, slew rate (SR+) of +71.2V/µS, THD of -63dB and DC consumption power (PC) of 2mW.

Keywords: pseudo-OTA used CMOS CFOA, low power CFOA, high-performance CFOA, novel CFOA

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

Abstract:

Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: Djalal Boualili

Abstract:

This article considers the problem of sizing prime movers for combined heating and power (CHP) systems operating at full load to satisfy a fraction of a facility's electric load, i.e. a base load. Prime mover sizing is examined using three criteria: operational cost, carbon dioxide emissions (CDE), and primary energy consumption (PEC). The sizing process leads to consider ratios of conversion factors applied to imported electricity to conversion factors applied to fuel consumed. These ratios are labelled RCost, R CDE, R PEC depending on whether the conversion factors are associated with operational cost, CDE, or PEC, respectively. Analytical results show that in order to achieve savings in operational cost, CDE, or PEC, the ratios must be larger than a unique constant R Min that only depends on the CHP components efficiencies. Savings in operational cost, CDE, or PEC due to CHP operation are explicitly formulated using simple equations. This facilitates the process of comparing the tradeoffs of optimizing the savings of one criterion over the other two – a task that has traditionally been accomplished through computer simulations. A hospital building, located in Chlef, Algeria, was used as an example to apply the methodology presented in this article.

Keywords: sizing, heating and power, ratios, energy consumption, carbon dioxide emissions

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Authors: Haniye Dehestani, Yadollah Ordokhani

Abstract:

In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: collocation method, fractional partial differential equations, legendre-laguerre functions, pseudo-operational matrix of integration

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Authors: Shubham Jaiswal

Abstract:

During modeling of transport phenomena in porous media, many nonlinear partial differential equations (NPDEs) encountered which greatly described the convection, diffusion and reaction process. To solve such types of nonlinear problems, a reliable and efficient technique is needed. In this article, the numerical solution of NPDEs encountered in porous media is derived. Here Jacobi collocation method is used to solve the considered problems which convert the NPDEs in systems of nonlinear algebraic equations that can be solved using Newton-Raphson method. The numerical results of some illustrative examples are reported to show the efficiency and high accuracy of the proposed approach. The comparison of the numerical results with the existing analytical results already reported in the literature and the error analysis for each example exhibited through graphs and tables confirms the exponential convergence rate of the proposed method.

Keywords: nonlinear porous media equation, shifted Jacobi polynomials, operational matrix, spectral collocation method

Procedia PDF Downloads 439