Identification and prioritization of factors affecting the transition to renewables in developing economies

Proceedings of the 7th International Conference on Advances on Clean Energy Research, ICACER 2022, April 20–22, 2022, Barcelona, Spain.DATA AVAILABILITY : No data was used for the research described in the article.There is a rapid increase in energy demand across several developing economies all over the world. This can be attributed to population growth, industrialization, urbanization, globalization, and occasional unforeseen events such as the COVID-19 pandemic, in which operations, functions, and activities are mostly executed virtually. With a major transition to renewables by developed economies to meet their energy obligations and mitigate greenhouse gas (GHG) emissions, developing economies are left with no choice but to join the transition in a bid to uphold the United Nations’ Sustainable Development Goal 13 (SDG13-Climate Action). This study has identified and prioritized barriers to renewable energy transition in developing economies. The Hybrid Structural Interaction Matrix (HSIM) was utilized to employ the weight based prioritization model with hierarchical structural layout of the interacting renewable energy transition barriers. This study will be of great benefit to policymakers and academics in making informed decisions on measures to fast-track the transition to renewables in developing economies by considering weighted prioritized driving forces for optimum resource allocation.http://www.elsevier.com/locate/egyrhj2023Industrial and Systems Engineerin

Optimum predictive modelling for a sustainable power supply mix : a case of the Nigerian power system

Please read abstract in the article.https://www.elsevier.com/locate/esrhj2023Industrial and Systems Engineerin

Surface roughness prediction using a hybrid scheme of difference analysis and adaptive feedback weights

This research has presented an optimum model for surface roughness prediction in a shop floor machining operation. The proposed solution is premised on difference analysis enhanced with a feedback control model capable of generating transient adaptive weights until a converging set point is attained. The surface roughness results utilized herein were adopted from two prior experiments in the literature. The design of experiment herein is premised on three cutting parameters in both experimental scenarios viz: feed rate, cutting speed and depth of cut for experimental dataset one and cutting speed, feed rate and flow rate for experimental dataset two. Three experimental levels were considered in both scenarios resulting in twenty-seven outcomes each. The simulation trial anchored on Matlab software was divided into two sub-categories viz: prediction of surface roughness for cutting combinations with vector points off the edges of the mesh referred to as off-edge cutting combinations (Off-ECC) and recovery of cutting combinations with positions on the edges of the mesh referred to as on-edge cutting combinations (On-ECC). The proposed hybrid scheme of difference analysis with feedback control premised on the use of dynamic weights produced an accurate output in comparison with the abductive, regression analysis and artificial neural network techniques as earlier utilized in the literature. The novelty of the proposed hybrid model lies in its high degree of prediction and recovery of existing datasets with an error margin approximately zero. This predictive efficacy is premised on the use of set points and transient dynamic weights for feedback iterations. The proposed solution technique in this research is quite consistent with its outputs and capable of working with very small to complex datasets.http://www.cell.com/heliyonam2022Industrial and Systems Engineerin

Virtual obstacles for sensors incapacitation in robot navigation : a systematic review of 2D path planning

The field of mobile robot (MR) navigation with obstacle avoidance has largely focused on real, physical obstacles as the sole external causative agent for navigation impediment. This paper has explored the possible option of virtual obstacles (VOs) dominance in robot navigation impediment in certain navigation environments as a MR move from one point in the workspace to a desired target point. The systematically explored literature presented reviews mostly between the years 2000 and 2021; however, some outlier reviews from earlier years were also covered. An exploratory review approach was deployed to itemise and discuss different navigation environments and how VOs can impact the efficacy of both algorithms and sensors on a robotic vehicle. The associated limitations and the specific problem types addressed in the different literature sources were highlighted including whether or not a VO was considered in the path planning simulation or experiment. The discussion and conclusive sections further recommended some solutions as a measure towards addressing sensor performance incapacitation in a robot vehicle navigation problem.The Department of Industrial and Systems Engineering, University of Pretoria.https://www.mdpi.com/journal/sensorsam2023Industrial and Systems Engineerin

Oxidative roasting experimentation and optimum predictive model development for copper and iron recovery from a copper smelter dust

Please read abstract in the article.The Council for Scientific and Industrial research (CSIR)http://www.editorialmanager.com/rineng/Default.aspxhj2021Industrial and Systems Engineerin

Parametric optimization and statistical evaluation of a spray dryer for the evaporation of caustic soda solution

Optimum evaporation of a 50% w/w caustic soda solution with a spray dryer was investigated in this work to enhance performance and statistically evaluate process parameters. Application of suitable model with validation, fabrication and operation within predicted optimum values enabled high performance, productivity and energy conservation. The highest exit mass flow rate of NaOH was 0.0459 kg/s, depicting 12% better value than the computed optimum value. The highest value of 73.85% was obtained for the exit final NaOH weight percent. Improvement over conventional multiple effect evaporators to obtain 73% w/w NaOH solution resulted in energy savings of about 2.34 106 J/kg (about 99.6565% specific energy savings). Statistical evaluation of process parameters using Analysis of Variance (ANOVA), Bonferroni-Holm, Holm-Sidak and Tukey Posthoc parametric tests enabled the confirmation of significant relationships among operating variables. The outcome indicated the possibility of better attainments in the field.The Central Research Committee of the University of Lagos, Nigeriahttps://www.heliyon.comam2020Industrial and Systems Engineerin

Identification and prioritization of factors affecting the transition to renewables in developing economies

There is a rapid increase in energy demand across several developing economies all over the world. This can be attributed to population growth, industrialization, urbanization, globalization, and occasional unforeseen events such as the COVID-19 pandemic, in which operations, functions, and activities are mostly executed virtually. With a major transition to renewables by developed economies to meet their energy obligations and mitigate greenhouse gas (GHG) emissions, developing economies are left with no choice but to join the transition in a bid to uphold the United Nations’ Sustainable Development Goal 13 (SDG13-Climate Action). This study has identified and prioritized barriers to renewable energy transition in developing economies. The Hybrid Structural Interaction Matrix (HSIM) was utilized to employ the weight based prioritization model with hierarchical structural layout of the interacting renewable energy transition barriers. This study will be of great benefit to policymakers and academics in making informed decisions on measures to fast-track the transition to renewables in developing economies by considering weighted prioritized driving forces for optimum resource allocation

Virtual Obstacles for Sensors Incapacitation in Robot Navigation: A Systematic Review of 2D Path Planning

The field of mobile robot (MR) navigation with obstacle avoidance has largely focused on real, physical obstacles as the sole external causative agent for navigation impediment. This paper has explored the possible option of virtual obstacles (VOs) dominance in robot navigation impediment in certain navigation environments as a MR move from one point in the workspace to a desired target point. The systematically explored literature presented reviews mostly between the years 2000 and 2021; however, some outlier reviews from earlier years were also covered. An exploratory review approach was deployed to itemise and discuss different navigation environments and how VOs can impact the efficacy of both algorithms and sensors on a robotic vehicle. The associated limitations and the specific problem types addressed in the different literature sources were highlighted including whether or not a VO was considered in the path planning simulation or experiment. The discussion and conclusive sections further recommended some solutions as a measure towards addressing sensor performance incapacitation in a robot vehicle navigation problem

Performance evaluation of the supply chain system of a food product manufacturing system using a questionnaire-based approach

Effective management of the end-to-end process of a food industry is vital for the achievement of the key strategic objectives of this organisation. However, various factors have limited the performance and productivity of the supply chain system of food industries; thus hindering an organisation from meeting its customers demand target. Hence; there is a need to appraise the performance of the supply chain system of a food industry with a view to identify factors limiting its performance and ensure continuous end-to-end process improvement. In light of this, this paper assesses the performance of the supply chain system of a food industry using a questionnaire-based approach. The structure of the questionnaire consists of myriad of questions that appraises the performance of various factors responsible for effective functioning and optimal flow of the supplier and production sections of the supply chain of a food industry based on the industry benchmark for these factors. The production operators responded to the appropriate sections of the questionnaire. The questionnaire result revealed that the overall performance of work stations 1, 3, 4 and 5 are below the organisation’s target. Hence, the resolutions of various factors lowering the performance of these work stations were recommended as future studies. The questionnaire developed in this study serve as a template that could be used by supply chain managers to measure the performance of their supply chain systems, with a view to ensure continuous and sustainable end-to-end process improvement.https://www.journals.elsevier.com/procedia-manufacturingam2021Industrial and Systems Engineerin

Development of a tool cost optimization model for stochastic demand of machined products

Cutting tool management in manufacturing firms constitutes an essential element in production cost optimization. In order to optimize the cutting tool stock level while concurrently minimizing production costs, a cost optimization model which considers machining parameters is required. This inclusive modeling consideration is a major step towards achieving effectiveness of cutting tool management policy in manufacturing systems with stochastic driven policies for tool demand. This paper presents a cost optimization model for cutting tools whose utilization level is assumed to be optimized in respect of the machining parameters. The proposed cost model in this research incorporated the effects of diversified machining costs ranging from operational through machining, shortage, holding, material and ordering costs. The machining of parts was assumed to be a single cutting operation. Holt-Winters forecasting technique was used to create a stochastic demand dataset for a test scenario in the production of a high-end automotive part. Some numerical examples used to validate the developed model were implemented to illustrate the optimal machining and tool inventory conditions. Furthermore, a sensitivity analysis was carried out to study the influence of varying production parameters such as: machine uptime, demand and cutting parameters on the overall production cost. The results showed that a desired low level of tool storage and holding costs were obtained at the optimal stock levels. The machining uptime had a significant influence on the total cost while tool life and cutting feed rate were both identified as the most influential cutting variables on the total cost. Furthermore, the cutting speed rate had a marginal effect on both costs and tool life. Other cost variables such as shortage and tool costs had significantly low effect on the overall cost. The output trend showed that the feed rate is the most significant cutting parameter in the machining operation, hence influencing the cost the most. Also, machine uptime and demand significantly influenced the total production cost.https://www.scirp.org/journal/AMam2019Industrial and Systems Engineerin