Integrating Statistical Process Control, Engineering Process Control And Taguchi'S Quality Engineering

In this paper, a scheme is proposed to integrate statistical process control (SPC), engineering process control (EPC) and Taguchi's quality engineering (TQE). Then, two models are proposed to implement the proposed scheme. The models employ the concept of Taguchi's quadratic loss function to determine whether to take an EPC action by comparing the cost of the action and the cost of quality. A case study is used to compare these two models with the model in the literature where SPC and EPC have been integrated. The results have shown that the first model resulted in about a 25% saving and the second model resulted in even greater saving of about 30% for the case under consideration

Integrating Quality And Maintenance Decisions In A Production- Inventory Model For Deteriorating Items

In typical production-inventory models of deteriorating items, deterioration of the production process has not been considered. In this paper, a model is proposed in which both the produced items and the production equipment deteriorate. When the production system deteriorates, it shifts to an out-of-control state and begins to produce a proportion of defective items, necessitating corrective maintenance action. A model is formulated to integrate several realistic aspects, including item and process deterioration, varying demand and production rates, quality, inspection, and maintenance. A heuristic solution algorithm is developed to determine the production and inspection schedules, and a numerical example is solved

Integrating Statistical Process Control, Engineering Process Control And Taguchi'S Quality Engineering

In this paper, a scheme is proposed to integrate statistical process control (SPC), engineering process control (EPC) and Taguchi's quality engineering (TQE). Then, two models are proposed to implement the proposed scheme. The models employ the concept of Taguchi's quadratic loss function to determine whether to take an EPC action by comparing the cost of the action and the cost of quality. A case study is used to compare these two models with the model in the literature where SPC and EPC have been integrated. The results have shown that the first model resulted in about a 25% saving and the second model resulted in even greater saving of about 30% for the case under consideration

Integrating Quality And Maintenance Decisions In A Production- Inventory Model For Deteriorating Items

In typical production-inventory models of deteriorating items, deterioration of the production process has not been considered. In this paper, a model is proposed in which both the produced items and the production equipment deteriorate. When the production system deteriorates, it shifts to an out-of-control state and begins to produce a proportion of defective items, necessitating corrective maintenance action. A model is formulated to integrate several realistic aspects, including item and process deterioration, varying demand and production rates, quality, inspection, and maintenance. A heuristic solution algorithm is developed to determine the production and inspection schedules, and a numerical example is solved

The inclusive analysis of ICT ethical issues on healthy society: a global digital divide approach

The Global Digital Division remains as a rising focus that has to be brought into the notice of the United Nations UN. It is about the vast disparity in exposure to the existing digital knowledge by ICT information and communication technologies amongst developed and developing nations. The work outlined here seeks to acknowledge the effects and provide feedback of an ethical issue on key areas. The study also provides information about the several concrete solutions to this issue in order to ensure the sustainable development of society. In addition, a Digital Effectiveness Framework has been suggested which consist of five phases namely access, exploration, knowledge acquisition, adoption, and innovation and transformation. The study ends with the molds that leads to address the impact of the Global Digital Divide will continue at national level. National surveillance systems must be set to determine the digital opportunity index DOI for each country and track their role as tech giants in the information and communication technology environment

Comparative analysis of public transport modes available in Karachi, Pakistan

This study presents a comparative analysis of selected parameters of existing formal and informal Public Transport (PT) modes being operated on three different types of fuels. The performance of PT modes is analysed on fuel consumption, capacity, transportation cost, and emissions resulting from these modes. The required data were collected using route-check survey method and conducting a questionnaire-based survey from drivers and operators of these modes. Furthermore, the performance of proposed buses for an under-construction BRT corridor is also evaluated and compared with the existing PT modes. The comparative analysis of the existing PT modes in Karachi shows that CNG operated PT modes are economically more efficient, which caused the conversion of diesel engines of buses and minibuses to CNG fuelled-engines. The study, for the first time, evaluates and compares the performance of informal PT mode (chingchi) with other modes of PT. Results show that the PT modes with less capacity, such as chingchi, should be discouraged due to their comparatively lower performance on the selected parameters. This study can be used by the authorities to analyze the performance of existing modes and prioritize the PT modes for future planning

Electricity energy dataset “BanE-16”: Analysis of peak energy demand with environmental variables for machine learning forecasting

The “BanE-16” dataset is a comprehensive repository integrating electricity grid dynamics with meteorological variables for machine learning-based energy forecasting. Featuring peak energy demand, environmental factors (temperature, wind speed, atmospheric pressure), and electricity generation statistics, this dataset enables intricate analysis of weather-energy correlations. Its multidimensional nature facilitates predictive modeling, exploring intricate dependencies, and optimizing energy infrastructure. Leveraging machine learning methodologies, this dataset stands as a catalyst for innovative forecasting models and informed decision-making in energy management. Its diverse variables offer a holistic perspective, empowering researchers to delve into nuanced interrelationships, paving the way for sustainable energy planning and predictive analytics in dynamic energy ecosystems. Its multivariate nature empowers sophisticated machine-learning models, enabling precise energy forecasts and infrastructure optimizations. Researchers leveraging this dataset unlock the potential to delve deeper into intricate weather-energy relationships, driving advancements in predictive analytics for sustainable energy management. The integration of diverse variables lays the groundwork for innovative methodologies, steering the trajectory of informed decision-making in dynamic energy landscapes