The spread of a respiratory syndrome known as Coronavirus Disease 2019 (COVID-19) quickly took on pandemic proportions, affecting over 192 countries. An emergency of the health system was obligated for the response to this epidemic. Although containment measures in China reduced new cases by more than 90%, the levels of reduction were not the same in other countries. So, the question that arises is: what the world will see this pandemic, and how many patients can be affected? The response would be helpful and supportive of the authority and the community to prepare for the coming days. In this study, the Autoregressive Integrated Moving Average (ARIMA) model was employed to analyze the temporal dynamics of the worldwide spread of COVID-19 in the time window from January 22, 2020 to April 7, 2020. The cumulative number of confirmed Covid-19-affected patients forecasted over the three months was between 9,189,262 – 14,906,483 worldwide. This prediction value of Covid 19-affected patients will be valid only if the situation remains unchanged, and the epidemic spreads according to the previous nature worldwide in these three months.

Electric vehicle (EV) has made a revolution in the automobile industry. The largest automobile industries are moving toward this. Within the next 5–10 years, the world will shift to EVs. Bangladesh is one of the emerging countries in Asia, so it will have great market potentiality. Bangladesh will have a big opportunity for EV business. However, there are some challenges too to introduce a new business model like EV business. In this study, we have tried to analyze the market potentiality and the business strategy in Bangladesh through strengths, weaknesses, opportunities, and threats analysis and analytical hierarchy process to analyze different strategies. These strategies had a feasible solution proved by sensitivity analysis.

The furniture industry is growing to a great extent in Bangladesh. Many market researchers believe that the industry has enormous potentiality. However, the expansion of this industry may face complexities within a few years. Due to the wrong selection of facilities, many organizations failed to earn profit as expected. It also needs a large investment. Selecting a suitable place for a new facility is going to be the biggest question of upcoming years. This study aimed to analyze Bangladesh’s furniture industry, address the facility location problem, and provide a constructive solution to the decision-makers. In this study, seven criteria were considered: availability of raw materials, transportations, skilled labor, proximity to customers, energy availability, economic zone facility, and environmental impact, and five ideal locations or alternatives: Khulna, Chattogram, Bogura, Gazipur, and Manikganj. Thirty-four experts took part in the survey to analyze the significant criteria for selecting a furniture industry’s facility location and alternatives or potential locations for the facility. The Analytical Hierarchy Process (AHP) and Fuzzy AHP methods (FAHP), two MCDM techniques, were used to analyze the data set. A sensitivity analysis was done to determine the model’s robustness for any critical changes in the real world. The result showed that ‘energy availability is the most significant criterion to select a facility location for the furniture industry, where it got 35.1% criteria weight in AHP and 33.9% in FAHP. ‘Chattogram’ was selected as the most suitable place containing 33.74% normalized weight in AHP and 33.81% normalized weight in FAHP.

Bangladesh’s government had been constantly conscious of its health-care system. As a result, the health-care system had seen a significant rise in quality in the past few years. The Lean Six Sigma concept is used to boost up the productivity as well as the quality of products or services. The purpose of this article was to measure the process capability in the health-care system by lean tools. In this study, we selected the dialysis unit as our investigation area where we applied the Six Sigma DMAIC (Define, Measure, Analysis, Improve, and Control) model which had been structured step by step, respectively. Furthermore, different tools of Total Quality Management, Statistical Quality Control and Lean manufacturing like SIPOC (Supplier, Input, Process, Output, and Customer) diagram, P Control chart, Fishbone diagram, and Pareto analysis had been performed in different phases of the DMAIC model. Measuring process capability using the DMAIC model helped to identify the problems associated with the dialysis unit and also recommendations were developed based on investigation and analysis. These recommendations will help the hospital management to overcome all problems and increase service rate and patient safety in the dialysis unit.