Manufacturing facilities are systems that require adequate designing, maintenance and reservations for improvement in the future. Layouts need to be effectively designed to reduce operating to the minimum. Computer simulation is a process of investigating and analyzing the behavior of production processes for effective decision-making using computers to generate solutions that will positively impact short, and long-term planning of the Plants and save costs of real-life implementation. This study investigated a 500Kg capacity shea nut processing plant using FlexSim©. The findings from the initial model were not effective and experienced bottlenecks in workstations (Roaster and Milling) sections, poor cycle and lead times coupled with manual labor, Plant efficiency was 35.7%. However, the Improvement Layout Model was able to address these bottlenecks, the results showed the Plant efficiency increased to 83.3%, shorter lead and cycle times, improved machine utilization, and throughput capacity of the Plant. The results were an indication of conformance to the layout design developed to aid in enhancing the traditional shea nut processing that is largely dominated by traditional processing practices.

The trend toward sustainable city development is associated with intelligent transportation systems (ITS). Automation, efficiency, safety, security, and cost-effectiveness are critical factors in establishing each aspect of a smart city. Real-time data obtained from ITS play an essential role in improving the level of service of road segments, enhancing road safety, and supporting road users with road circumstances information. Travel time information is applicable in travel time maps, decision makings for traffic congestion, dynamic pricing of the network, emergency relief services, traffic flow monitoring, traffic jams management, and air quality analysis. Travel time on a road segment highly depends on geometrical specifications, environmental and weather conditions, traffic flow, and driving behavior. Due to specific driving behavior and road conditions, the above parameters are not essentially applicable in another region. The present research uses the data collected from loop detectors and License Plate Recognition (LPR) systems to develop a Bureau of Public Roads (BPR) model for Iran’s freeway network (Tehran-Qom Freeway). Because of the large amount of data, the SQL server program was used for creating and organizing the database and the BPR model was calibrated using SPSS statistical software. The results of the BPR model were evaluated with an ANOVA test, indicating that the derived model can estimate the travel time at freeway sections with a %5.2 error for the volume-to-capacity ratio (V/C) of less than 0.8.

The ready-to-wear sector is expanding quickly and already accounts for a significant contribution to Ethiopia's export revenue. Due to its lower labor and investment costs, availability of resources, government assistance, etc. than other sectors, this industry attracts young entrepreneurs from around the nation as investment destinations. However, while investing in the leather industry, there are frequently many more aspects to consider. Again, there are numerous leather investment opportunities in the leathers sector, including handbags, jackets, belts, shoes, gloves, etc. Different sorts of leather items necessitate various levels of capital investment, operator skill sets, and resource requirements, among many other things. Again, based on their capacity for managing businesses, available capital, business location, and other factors, not all investors are in the same position. To assist investors in making decisions on the opening of a new leather industry, this paper presents a FAHP methodology for choosing the best leather item among various possibilities in a fuzzy environment. The methods enable the decision-maker to incorporate language expressions of expert judgment into the evaluation process. Using the suggested process, the ideal leather item is chosen for the launching of a leather industry in Ethiopia under the current circumstances.

The world is increasingly witnessing food insecurity and deteriorating individual and global livelihoods. This study sought to assess the effectiveness of contract farming in the form of command farming in achieving sustainability of maize supply chain in Zimbabwe. A descriptive approach was adopted where a sample of 35 agricultural experts were randomly selected to respond to questionnaires. The researchers also relied on interviews with farmers, the results of which were triangulated with quantitative data to improve the dependability of results. The study shows a positive and significant relationship between command farming and sustainability of the maize supply chain in Mazowe district of Zimbabwe. The study, therefore, recommends the government to invest more in command agriculture to improve productivity and sustainability in the maize sector. It further recommends investment in joint contract farming with agricultural firms and government to improve farming business to sustain the country’s agricultural sector.

During the last decades, environmental crises through energy consumption and economic growth were noticed as a growing concern among researchers. The industrial sector is the main part of economic growth in each country using conservative energy and emitting carbon dioxide that causes global warming. The Paris agreement and Kyoto protocol were two agreements to prevent governments from emitting CO2 freely. Purpose of this research was to investigate the cement industry, steel industry, and automobile industry products’ effects on CO2 emissions in Iran and to rank them according to their measured effects on CO2 emissions. The methodology used in this study was to estimate equations with CO2 emissions as a dependent variable and cement, steel, and automobile industries’ products with ordinary least squares (OLS) and generalized moment method (GMM) approaches. Stationary, Johansen cointegration, Durbin-Watson, Breusch-Godfrey, Chow breakpoint, and normal residual tests were checked. In-sample forecasting was implemented to check the precision of the estimation and an updated ranking was reported as a final result to consider which industry has affected CO2 emissions more than the others per unit of production cost. In conclusion, the cement industry, steel industry, and automobile industry had the most positive effects on CO2 emissions, respectively. This result is suitable to prioritize the industries for enhancing green technology and optimizing industrial production for a more sustainable economy.