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Item Design sustainability of reconfigurable machines.(Institute of Electrical and Electronics Engineers, 2020-11-03) Olabanji, Olayinka Mohammed; Mpofu, KhumbulaniThis paper presents the sustainability assessment for reconfigurable machines based on cosine similarity measures and Euclidean distances. The methodology entails the application of four peculiar sustainability indicators (Reconfigurability, Manufacturing, Functionality, and Life Cycle Analysis) that are suitable for reconfigurable machines alongside the traditional sustainability indicators (Environmental, Social, and Economic). An index relating chart approach is proposed for determining the indices of the peculiar and traditional sustainability indicators and their sub-indicators. The chart involves the identification of viable links of the sub-indicators of an indicator and the sub-indicators of other indicators. The viable links are fuzzified using the fuzzy trapezoidal set because of the multi-dimensions and units of the sustainability indicators. The cosine similarity measures of the sustainability indicators were aggregated to estimate the sustainable similarity measures of the reconfigurable machines while the Euclidean distance estimates the distances of the indicators to best and worst sustainable performance in order to identify the sustainability indicators for improvement. Experts’ opinions are applied to appraise the availability of sub-indicators in the four reconfigurable machine prototypes (vibrating screen, assembly fixture, bending press machine, and flexible fixture) used as case studies. A sensitivity analysis was carried out to validate the computational process of the methodology. The sensitivity analysis shows that the application of cosine similarity measures is suitable for assessment of sustainability considering the closeness of the similarity measures for the defuzzified values of the trapezoidal fuzzy numbers and the cosine similarity values of the aggregating matrix of the indicators. Also, the findings that can be deduced from the results of the appraisal of the case studies presented in this article shows that high sustainable index and similarity measures can be achieved by creating a balance in the performance of all the sustainable indicators. The results from the assessment also support the fact that improving one sustainability indicator because of its closeness to the worst sustainable performance may cause other indicators not to perform satisfactorily.Item Development of numerical model for the prediction of temperature and surface roughness during the machining operation of titanium alloy (Ti6A14V).(Czech Technical University in Prague, 2020-11-02) Daniyan, Ilesanmi; Tlhabadira, Isaac; Mpofu, Khumbulani; Adeodu, AdefemiTemperature and surface roughness are important factors, which determine the degree of machinability and the performance of both the cutting tool and the work piece material. In this study, numerical models obtained from the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques were used for predicting the magnitude of the temperature and surface roughness during the machining operation of titanium alloy (Ti6Al4V). The design of the numerical experiment was carried out using the Response Surface Methodology (RSM) for the combination of the process parameters while the Artificial Neural Network (ANN) with 3 input layers, 10 sigmoid hidden neurons and 3 linear output neurons were employed for the prediction of the values of temperature. The ANN was iteratively trained using the Levenberg-Marquardt backpropagation algorithm. The physical experiments were carried out using a DMU80monoBLOCK Deckel Maho 5-axis CNC milling machine with a maximum spindle speed of 18 000 rpm. A carbide-cutting insert (RCKT1204MO-PM S40T) was used for the machining operation. A professional infrared video thermometer with an LCD display and camera function (MT 696) with infrared temperature range of −50−1000 °C, was employed for the temperature measurement while the surface roughness of the work pieces were measured using the Mitutoyo SJ – 201, surface roughness machine. The results obtained indicate that there is high degree of agreement between the values of temperature and surface roughness measured from the physical experiments and the predicted values obtained using the ANN and RSM. This signifies that the developed RSM and ANN models are highly suitable for predictive purposes. This work can find application in the production and manufacturing industries especially for the control, optimization and process monitoring of process parameters.Item The use of analytical hierarchy process (AHP) decision model for materials and assembly method selection during railcar development.(Taylor and Francis Group, 2020-10-01) Daniyan, Ilesanmi; Mpofu, Khumbulani; Ramatsetse, BoitumeloThe need for improved performance, operational efficiency as well as cost and environmental sustainability necessitate the selection of appropriate materials and assembly methods during railcar manufacturing and maintenance. The selection of the most appropriate materials and assembly methods amidst different materials is a Multi-Criteria Decision (MCD) which requires a scientific decision support framework. In this study, a model based on the Analytical Hierarchy Process (AHP) was used for the selection of the most suitable material and method of assembly for the development and maintenance of the body shell of a railcar. The performance of stainless steel, aluminum and carbon steel as well as welding methods such as Laser Arc Welding (LAW), Friction Stir Welding (FSW) and Metal Inert Gas (MIG) and the Resistance Spot Welding (RSW) currently used in railcar development were examined. The strength to weight ratio, crash worthiness, mechanical properties, degree of formability as well as cost effectiveness, end of life, and functional requirements were the key decision variables that form the criteria, which were broken down into a number of sub-criteria. The criteria and subcriteria were pairwise compared to determine their priorities to the design an service requirements (goal). The AHP gave a detailed analysis of the materials as well as the methods of assembly that meet the service requirements of the railcar in a hierarchical order. Hence, this work provides the application of decision support framework for meeting the increasing design and service requirements in the railcar manufacturing industries.Item Numerical modeling and validation of Aluminium Friction Stir Welding (FSW) process during railcar manufacturing.(Elsevier, 2020-01-01) Daniyan, Ilesanmi; Mpofu, Khumbulani; Ramatsetse, Boitumelo; Phuluwa, Humbulani SimonInnovative joint design and optimization of the welding procedure for Friction Stir Welding (FWS) during railcar manufacturing will improve the overall cost effectiveness and crashworthiness of the assembled parts. In this work, the combination the Taguchi method and Finite Element Analysis (FEA) approaches were employed for the optimization of the Friction Stir Welding (FWS) of aluminum alloy during railcar manufacturing. The FEA approach was used to investigate the thermo-mechanical behavior of the material during the welding operation while the experiment designed with the use of the Taguchi methodology was used as a guide to perform the physical welding operations in the following range: welding speed (8–20 mm/s); rotational speed (400–700 rpm); frictional pressure (20–40 MPa); and friction time (4–10 s) The statistical analysis of the results obtained was used to obtain a mathematical model which correlates distortion as a function of the independent process parameters. The results obtained indicate that the development of a welded joint with high structural integrity that will meet the service requirements. The results also show that the magnitude of the distortions determined from the computer aided modeling and simulation were lesser than the ones obtained from the physical experiments. However, the values of distortion obtained from the predicted model was were found to be in good agreement with the physical experimental values. The combination of these techniques will assist manufacturers as a decision making tool in their quest for the development of welded structures of high integrity.Item Effect of sintering temperatures on the properties of in‑situ copper‑niobium‑titanium di‑boride composites.(MDPI, 2020-11-25) Eze, Azunna Agwo; Sadiku, Emmanuel Rotimi; Kupolati, Williams Kehinde; Snyman, Jacques; Ndambuki, Julius Musyoka; Jamiru, Tamba; Durowoju, Mondiu Olayinka; Ibrahim, Idowu David; Shongwe, Mxolisi Brendon; Desai, Dawood A.; Machaka, Ronald; Mpofu, KhumbulaniThis work investigated the effect of the sintering temperatures on the densifcation of the powders, density, relative density, microhardness, coeffcient of thermal expansion, and corrosion resistance in sulphuric acid solution environment of copper-niobium-titanium di-boride composite. A 90% weight of copper, reinforced with a 6% weight of niobium micro-particles and 4% weight of titanium-diboride was prepared in powdered form and sintered in two different temperatures of 650 °C and 700 °C using the spark plasma sintering method. The crystal phases and the morphologies of both the starting powders and the sintered samples were analyzed by the use of X-ray diffraction with copper Alpha-K radiation and scanning electron microscopy with energy dispersive X-ray spectroscopy. The results show that sintering at a temperature of 700 °C reduced the displacement rate of the powders with a higher microhardness value of 941 MPa when compared with the sintering temperature of 650 °C, which prolonged the displacement rate of the powders with a lower microhardness value of 827 MPa. The sintered samples recorded negative thermal expansion values of−1.375×10−5 °C−1 and−7.780×10−6 °C−1 at temperatures of 650 °C and 700 °C, respectively. The sample sintered at 700 °C has better micro-hardness and better corrosion resistance in a sulphuric acid environment when compared to the one sintered at 650 °C. This study has shown that the varying of the sintering temperatures has an effect on the properties of the composite under study. The produced composites can be used to control the mechanical and electrical properties, and the thermal expansion of functional materials, such as superconductors, semiconductors, ferroelectrics, magnetic and Mott insulators, etc.Item An approach for enhancing optimal resource recovery from different classes of waste in South Africa: Selection of appropriate waste to energy technology.(Elsevier, 2020-06-11) Adenuga, Olukorede Tijani; Mpofu, Khumbulani; Modise, Kgaugelo RagoseboThe need for effective municipal solid waste (MSW) management in an environmentally friendly, technologically viable, economically feasible and socially acceptable way presents a major global challenge. Planning of MSW management for municipalities require periodical evaluation of technology performance should consider the full waste hierarchy towards an enabling action for reduction, reusing and recycling in provision of energy and secondary raw materials for sustainable development. Decision support model is an integrated approach to enhance optimal resource recovery from different classes of waste for optimal economic importance, technical possibilities, environmental impact and sociocultural implication. The paper proposed a decision support model for selecting appropriate technology using approximation method for pairwise and normalized comparison matrix for Analytical Hierarchy Process (AHP) with subjective judgement of the sustainable indicators for different classes of waste in Western Cape municipality and six other urban areas. Among the four technologies, Anaerobic Digestion (AD) is ideal for the conversion of WtE with overall scoring of 57%, based on positive impact on the environment compared to Incineration (24%), Gasification (13%) and Pyrolysis (6%). The sustainable indicators criteria results revealed priority vector score for Environment as 0.4537, followed by Sociocultural at 0.2495, Economical at 0.2168 and Technical at 0.0800. The sensitivity coefficient for CR at 1 0,277 for technology and 0,238 for cost with preference to AD for the Western Cape Municipality in South Africa. This is important for policymakers in technology selection decisions support for MSWtE in similar contexts of the developing world.Item Sustainable demanufacturing model for promoting circular economy in the rail industry.(Elsevier, 2020-01-01) Phuluwa, Humbulani Simon; Daniyan, Ilesanmi; Mpofu, KhumbulaniRail industry across the globe is growing exponentially since the days of rail inception into African transportation systems. Freight and passenger trains contribute a greater proportion to rail industry commercial structures. The passenger trains are a mode of transport for both poor and rich people in Africa. Due to the lack of appropriate end-of-life (Eol) recovering strategies of the train’s components, most components are relegated to landfills. Most African countries including South Africa have been importing trains for many years, primarily from Europe and Asia. Some of these trains have reached or are reaching Eol soon, which makes it difficult for countries to develop or have appropriate mechanisms or technologies of recovering Eol components. Moreover, lack of train manufacturing plants in some of African countries create a vacuum in recovering Eol components of the trains. This study will review various literature on train life cycle management system and end-of-life recovery strategies applied across the globe. The study further looks at different circular economy modalities, which can be best suited for the African environment. The novelty of this study is in a demanufacturing operation framework that is flexible on recovering complex Eol railcar components in the African region. The study will use a case study of Africa against the globe to assess the readiness of countries to gain benefits of circular economy. The study intends to develop a sustainable demanufacturing based conceptual model to promote circular economy.Item Optimal Trajectory Scheme for Robotic Welding Along Complex Joints Using a Hybrid Multi-Objective Genetic Algorithm.(Institute of Electrical and Electronics Engineers, 2019-10-20) Ogbemhe, John; Mpofu, Khumbulani; Tlale, NkgathoThe problem of trajectory planning is relevant for the proper use of costly robotic systems to mitigate undesirable effects such as vibration and even wear on the mechanical structure of the system. The objective of this study is to design trajectories that are devoid of collision, velocity, acceleration, jerk and snap discontinuities so that the cycle time required to complete the process can be reduced. The trajectory design was constructed for all the six joints, using a 9th order Bezier curve to accommodate the ten boundary conditions required to satisfy the continuity constraints for joints displacement, velocity, acceleration, jerk and snap. The scheme combines the multi-objective genetic algorithm and the multi-objective goal attainment algorithm to solve the problem of total tracking error reduction during arc welding. The use of a hybrid multi-objective algorithm shows an improved average spread, average distance, number of iteration and computational time. Also, it can be concluded from the constraints studied, that the optimal path in terms of the robots dynamic constraints can achieve the expected tracking ability in terms of the optimal joint angles, velocities, acceleration, jerk, snap and torque.Item Optimal location of landfills and transfer stations for municipal solid waste in developing countries using non-linear programming.(Elsevier, 2021-03-10) Monzambe, Giovani M.; Mpofu, Khumbulani; Daniyan, Ilesanmi A.The design of Municipal Solid Waste Management Systems (MSWMS) is one of the fields where optimization techniques have been used in different places. The aim of this study was to develop a mathematical model for the optimization of MSW Transportation System, in order to assist waste management institutions, and local governments to minimise waste transportation time and cost. Non-linear Mixed Integer mathematical model, with the objective function to minimize the time and cost of waste transportation, was developed and solved using Microsoft Excel solver. The developed model was applied to a case study city situated in South Africa. The application of this model to this case study has provided an approximate decrease in total transportation cost per week of 2.04%. The novelty of this research lies in the simplification of the existing mathematical model and the development of a new approach to solve the non-linear model.Item An Evaluation model for selecting part candidates for additive manufacturing in the transport sector.(MDPI, 2021-04-12) Muvunzi, Rumbidzai; Mpofu, Khumbulani; Daniyan, IlesanmiThere is a need to develop guidelines for identifying situations where it is more beneficial to apply Additive Manufacturing (AM) as opposed to conventional methods of manufacturing. Thus, the aim of this paper is to propose a model for evaluating the sustainability of applying AM in the manufacture of transport equipment parts. A literature review was conducted to identify the parameters for selecting the part candidates. In the next stage, the criteria were ranked according to the needs of the transport equipment manufacturing industry using the Analytical Hierarchy Process (AHP) technique. The next stage featured the development of the decision matrix using the weights and classified levels. To validate the proposed decision matrix, different case studies from literature were used. The weights obtained from the case studies were in agreement with the proposed evaluation model. This study will add to the understanding of how the AM industries can effectively screen potential part candidates, thereby promoting the overall sustainability of the AM process in terms of material conservation, geometric complexity and functionality. There is still a dearth of information on the evaluation models capable of identifying the core functions of the products and the applicable environment. The work presents a proposed framework for part selection using the evaluation model.Item Fusing multi-attribute decision models for decision making to achieve optimal product design.(Sciendo, 2020-09-28) Olabanji, Olayinka Mohammed; Mpofu, KhumbulaniManufacturers need to select the best design from alternative design concepts in order to meet up with the demand of customers and have a larger share of the competitive market that is flooded with multifarious designs. Evaluation of conceptual design alternatives can be modelled as a Multi-Criteria Decision Making (MCDM) process because it includes conflicting design features with different sub features. Hybridization of Multi Attribute Decision Making (MADM) models has been applied in various field of management, science and engineering in order to have a robust decision-making process but the extension of these hybridized MADM models to decision making in engineering design still requires attention. In this article, an integrated MADM model comprising of Fuzzy Analytic Hierarchy Process (FAHP), Fuzzy Pugh Matrix and Fuzzy VIKOR was developed and applied to evaluate conceptual designs of liquid spraying machine. The fuzzy AHP was used to determine weights of the design features and sub features by virtue of its fuzzified comparison matrix and synthetic extent evaluation. The fuzzy Pugh matrix provides a methodical structure for determining performance using all the design alternatives as basis and obtaining aggregates for the designs using the weights of the sub features. The fuzzy VIKOR generates the decision matrix from the aggregates of the fuzzified Pugh matrices and determine the best design concept from the defuzzified performance index. At the end, the optimal design concept is determined for the liquid spraying machine.Item Methodology for the design of a reconfigurable guillotine shear and bending press machine (RGS&BPM).(Emerald, 2020-10-31) Sibanda, Vennan; Mpofu, Khumbulani; Trimble, JohnPurpose – In manufacturing, dedicated machine tools and flexible machine tools are failing to satisfy the ever-changing manufacturing demands of short life cycles and dynamic nature of products. These machines are limited when new product designs are introduced. The solution lies in developing responsive machines that can be adjusted or be changed functionally when these change requirements arise. These machines are reconfigurable machines which are becoming the new focus, as they rapidly respond to product variety and volume changes. A sheet metal working machine known as a reconfigurable guillotine shear and bending press machine (RGS&BPM) has been developed. The purpose of this paper is to present a methodology, function-oriented design approach (FODA), which was developed for the design of the RGS&BPM. Design/methodology/approach – The design of the machine is based on the six principles of reconfigurable manufacturing systems (RMSs), namely, modularity, scalability integrability, convertibility, diagnosability and customisability. The methodology seeks to optimise the design process of the RGS&BPM through a design of modules that make up the machine, enable its conversion and reconfiguration. The FODA is focussed on function identification to select the operational function required. Two main functions are recognised for the machine, these being cutting and bending; hence, the design revolves around these two and reconfigurability. Findings – The developed design methodology was tested in the design of a prototype for the reconfigurable guillotine shear and bending press machine. The prototype is currently being manufactured and will be subjected to functional tests once completed. This paper is being presented not only to present the methodology by to show and highlight its practical applicability, as the prototype manufacturers have been enthusiastic about this new approach. Research limitations/implications – The research was limited to the design methodology for the RGS&BPM, the machine which has been designed to completion using this methodology, with prototype being manufactured. Practical implications – This study presents critical steps and considerations in the development of reconfigurable machines. The main thrust being to explore the best possibility of developing the machines with dual functionality that will assist in availing the technology to manufacturer. As the machine has been development, the success of the design can be directly attributed to the FODA methodology, among other contributing factors. It also highlights the significance of the principles of RMS in reconfigurable machine design. Social implications – The RGS&BM machine is an answer for the small-to-medium enterprises (SMEs), as the machine replaces two machines with one, and the methodology ensures its affordable design. It contributes immensely to the machine availability by eliminating trial and error approaches. Originality/value – This study presents a new approach to the design of reconfigurable dual machines using principles of RMS. As the targeted market is the SME, it is not limited to that as any entrepreneur may use the machine to their advantage. The design methodology presented contributes to the body of knowledge in dual reconfigurable machine tool design.Item Process Design for Milling Operation of Titanium Alloy (Ti6Al4V) Using Artificial Neural Network.(JMIR Publications, 2021-08-21) Daniyan, Ilesanmi Afolabi; Mpofu, Khumbulani; Tlhabadira, Isaac; Ramatsetse, Boitumelo InnocentTitanium alloy is characterized with excellent mechanical properties such as lightweight, and good corrosion resistance ability, hence, it finds application in many industrial and engineering applications. This study considers the process design of the milling operation of titanium alloy using artificial intelligence. The numerical experimentation involves the use of the Artificial Neural Network (ANN) back propagation and Levenberg Marquardt algorithm for the correlation of the process parameters while the physical experiments were investigated using a DMU80monoBLOCK Deckel Maho 5-axis CNC milling machine and carbide-cutting inserts of 12 and 14 mm (RCKT1204MO-PM S40T) under the cooling and dry machining conditions. The developed network was used to obtain a regression analysis which is suitable for the prediction of the feasible range of the process parameters. The results obtained from the physical experiments indicate significant reduction in the rate of tool wear under the cooling conditions as opposed to the dry machining. The findings of this work will find suitable application as a decision making tool in the manufacturing industries most especially the manufacturing industries, which employs titanium alloy for component part development.Item Review of life cycle models for enhancing machine tools sustainability: lessons, trends and future directions.(Elsevier, 2021-04-09) Daniyan, Ilesanmi; Mpofu, Khumbulani; Ramatsetse, Boitumelo; Gupta, MunishThe life cycle models are critical in the assessment of the performance of a product from the design phase to its end of life (EoL). With the quest for manufacturing sustainability with respect to energy, process, material, and environment friendliness as well as the clamour for circular economy which emphasizes zero tolerance for waste, there is a need for a critical review of the life cycle of machine tool employed for machining operations and product development. The objective of this study is to evaluate the efficient way of managing the machine tools throughout its lifecycle. Several studies have been conducted in analysing the life cycle of the machine tools and different strategies were employed for its design, manufacture, use, maintenance and recovery at the end of life. The common approach to ensure environmental sustainability was established when comparing the literature studied. From the articles reviewed 60% applied life cycle assessment (LCA) methodology to reduce energy consumption and enhance environmental sustainability, while 40% employed other assessment tools. In this study an integrated life cycle and cyber physical machine tool model is proposed.Item Pugh matrix and aggregated by extent analysis using trapezoidal fuzzy number for assessing conceptual designs.(Growing Science, 2020-01-01) Olabanji, Olayinka; Mpofu, KhumbulaniDeciding conceptual stage of engineering design to identify an optimal design concept from a set of alternatives is a task of great interest for manufacturers because it has an impact on profitability of the manufacturing firms in terms of extending product demand life cycle and gaining more market share. To achieve this task, design concepts encompassing all required attributes are developed and the decision is made on the optimal design concept. This article proposes the modeling of decision making in the conceptual design stage of a product as a multicriteria decision making analysis. The proposition is based on the fact that the design concepts can be decided based on considering the available design features and various sub-features under each design feature. Pairwise comparison matrix of fuzzy analytic hierarchy process is applied to determine the weights for all design features and their sub-features depending on the importance to the design features to the optimal design and contributions of the sub-features to the performance of the main design features. Fuzzified Pugh matrices are developed for assessing the availability of the sub-features in the design concept. The cumulative from the Pugh matrices produced a pairwise comparison matrix for the design features from which the design concepts are ranked using a minimum degree of possibility. The result obtained show that the decision process did not arbitrarily apportion weights to the design concepts because of the moderate differences in the final weights.Item Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept.(Elsevier, 2020-01-06) Olabanji, Olayinka Mohammed; Mpofu, KhumbulaniIn this article, a novel hybridized Multi-Attribute Decision Model (MADM) is developed to identify an optimal design of a Reconfigurable Assembly Fixture (RAF) from a set of alternative design concepts. The model combines the comparative advantage of Fuzzy Analytic Hierarchy Process (FAHP) and the computational strength of the Fuzzy Weighted Average (FWA) based on left and right scores in order to obtain aggregates for the design alternatives considering the relative importance of the design criteria as needed in the optimal design. The model was applied to evaluate four design concepts of a RAF with six design features having numerous sub-features. Results obtained from the evaluation process shows that there are differences in final values of the design alternatives. However, a close variation exists between these values. These differences can be accrued to the interrelationships between the design features and sub-features obtained from the Fuzzy Synthetic Extent (FSE) ofthe FAHP and an unambiguity judgment of the FWA when aggregating availability of the design features and sub-features in the design alternatives.Item Numerical and experimental analysis of surface roughness during the milling operation of titanium alloy Ti6Al4V.(Engineering and Technology Publishing, 2020-12-30) Daniyan, Ilesanmi Afolabi; Tlhabadira, Isaac; Mpofu, Khumbulani; Muvunzi, RumbidzaiTitanium alloy (Ti-6Al-4V) has many industrial applications due to its excellent mechanical properties. However, its low thermal conductivity often results in surface and dimensional inaccuracies during machining operations. In this study, an experimental investigation was done to characterise the influence of milling parameters on the surface roughness of Ti-6Al-4V. The numerical experimentation involves the use of the Response Surface Methodology (RSM) with three factors namely: the speed, feed and depth of cut. The physical experiments were carried out using a DMU80monoBLOCK Deckel Maho 5-axis CNC milling machine and a carbide-cutting insert (RCKT1204MO-PM S40T). The comparative analysis of the results obtained indicate that the milling parameters and cutting conditions significantly influenced the surface finish of the titanium alloy. The results obtained from the physical experiments indicate an increase in the magnitude of the surface roughness when the cutting parameters exceed their optimal values. The machining parameters which resulted in the least surface roughness (Ra: 0.035 µm, Rz: 1.12 µm and Rq: 0.277 µm) under the air cooling condition were: cutting speed (265 m/min), feed per tooth (0.05 mm) and depth of cut (0.5 mm). Information on the effect of machining parameters on surface roughness will assist manufacturers in selecting the most feasible combination of the process parameters for producing titanium alloy (Ti-6Al-4V) parts with improved surface quality.Item Energy and carbon emission efficiency prediction: Applications in future transport manufacturing.(MDPI, 2021-12-03) Modise, Ragosebo Kgaugelo; Mpofu, Khumbulani; Adenuga, TijaniThe long-term impact of high-energy consumption in the manufacturing sector results in adverse environmental effects. Energy consumption and carbon emission prediction in the production environment is an essential requirement to mitigate climate change. The aim of this paper is to evaluate, model, construct, and validate the electricity generated data errors of an automotive component manufacturing company in South Africa for prediction of future transport manufacturing energy consumption and carbon emissions. The energy consumption and carbon emission data of an automotive component manufacturing company were explored for decision making, using data from 2016 to 2018 for prediction of future transport manufacturing energy consumption. The result is an ARIMA model with regression-correlated error fittings in the generalized least squares estimation of future forecast values for five years. The result is validated with RSS, showing an improvement of 89.61% in AR and 99.1% in MA when combined and an RMSE value of 449.8932 at a confidence level of 95%. This paper proposes a model for efficient prediction of energy consumption and carbon emissions for better decision making and utilize appropriate precautions to improve eco-friendly operation.Item Robot dynamic model: freudenstein-based optimal trajectory and parameter identification.(Taylor and Francis Group, 2022-02-18) Ogbemhe, John; Mpofu, Khumbulani; Mokakabye, MabolayaA thorough understanding of an industrial robot’s dynamic model is critical for practical robotic applications. An effective dynamic model is required for optimal controller design and trajectory planning. Robot manufacturers only provide kinematic data, which can only guarantee a certain level of positioner accuracy. The design of the trajectory-planning scheme, on the other hand, necessitates a thorough understanding of its dynamic features. The identification of dynamic parameters involves several procedures. This study used the Euler-Lagrangian equation to derive the robot dynamic model in its canonical form. To excite each link of the irb1600 robot industrial robot while avoiding displacement, velocity, and acceleration discontinuities at the start and endpoints, a Freudenstein 1-3-5 trajectory based on Fourier series expansion was used. The dynamic parameters were determined using the nonlinear least-squares approach based on the Levenberg-Marquart equation. The Savitzky-Golay smoothing filters improved the identification method by decreasing system noise.Item An investigation of the effect of the ISO 9001 quality management system on the small and medium enterprises in Gauteng, South Africa.(The Southern African Institute for Industrial Engineering, 2022-03-08) Magodi, A.Y.; Daniyan, I.A.; Mpofu, K.The implementation of quality management systems (QMS) is central to the performance of small and medium enterprises (SMEs). At present, there is a lack of information about the level of adoption and implementation of QMS by SMEs in Gauteng Province, even though that province has the highest number of SMEs in South Africa (SA). This study therefore aims to investigate the effect of the ISO 9001 QMS on SMEs in Gauteng. Quantitative research was conducted, and an online survey was used to collect data. An inferential statistical data analysis involving the Statistical Package for the Social Sciences (SPSS) software was used to analyse the collected data. The chi-square and Fischer’s exact tests were applied to validate the statistical significance of four hypotheses. The inferential analysis showed that there is a relationship between ISO 9001 implementation and SMEs’ sustainability, as well as a direct relationship between the implementation of ISO 9001 and the performance, growth, and life span of SMEs in Gauteng Province. In addition, the results indicated that 64 per cent of the surveyed SMEs are aware ISO 9001, while 36 per cent of SMEs were not aware of QMS. The survey indicated that SMEs face several challenges, such as the ineffective implementation of QMS, poor funding, a low level of human capacity development, a lack of adequate resources, poor working environment, and poor work organisation, a lack of necessary materials, and the use of inappropriate work methods. It is envisaged that, if a culture of QMS were to be adopted and implemented by SMEs, there would probably be an improvement in operational efficiency, leading to improved customer satisfaction and increased turnover and profitability.
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