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Environmental management is a critical issue for the readymade garment (RMG) industry, as it is a significant contributor to environmental degradation and pollution. Effective environmental management planning (EMP) is crucial for RMG factories to reduce their environmental impact and promote sustainability. This research focuses on the development of a sustainable EMP as a case study for an RMG factory, intending to address the environmental challenges facing the industry. The factory was segmented into 24 different sections, and activities for each section were enlisted to determine their environmental impact. Using a risk matrix analysis, the study identified noise pollution from various sources, such as from winding, auto placket, back winding, electricity generator, and compressor section, as well as water pollution from the washing section and stack air emission from the generator and boiler section, as the biggest environmental risks. The findings of this study provide valuable insights into the environmental impact of the RMG industry, highlighting the challenges it faces in terms of sustainability. The study underscores the need for effective management strategies to address these challenges and promote sustainability. [ABSTRACT FROM AUTHOR]

The ready-made garment (RMG) industry is one of the largest industrial sectors in Bangladesh in terms of economy and employment. As the world economy moves forward, this highly people-dense industry needs to be digitalized. However, the importance of digital technology, particularly the Internet of Things (IoT), has just lately been recognized by most industries, which is also an important part of Industry 4.0. The IoT has seven important elements. Though IoT has the potential to grow businesses, it is difficult to implement all the elements of IoT simultaneously. Thus, the study aims to build a hierarchy model of IoT elements to be implemented in the RMG industry of Bangladesh. Through an extensive literature review, fourteen significant elements of IoT were identified. Then the study employs an integrated multi-criteria decision-making (MCDM) framework to rank the elements of IoT based on their potential for application in the Bangladeshi RMG industry. The weights of the evaluation criteria were determined using a fuzzy analytical hierarchy process (FAHP), and the elements of IoT were ranked using a preference ranking organization method for enrichment evaluations (PROMETHEE II) based on the criteria weights obtained from FAHP. The study findings suggest that the Sensors are the most significant component of IoT, while Network Interconnection is the least significant component for IoT implementation. This study is expected to assist the stakeholders in the RMG and other related industrial sectors in formulating appropriate strategies and policies for the proper deployment of IoT. [ABSTRACT FROM AUTHOR]

Readymade garment industry is one of the production industries in Bangladesh where various types of materials, components, procedures, actions and conditions are being used and so there is high possibility of accidents to occur. Sewing section in garment industry is concerned with different hazards and risks which have surely negative impact on the environment and health of the workers. The main reason of this paper is to find out the hazards and risks existing in a sewing section of a readymade garment industry located in Bangladesh. A hazard analysis worksheet will be prepared including hazardous events, causes, control measurements, likelihood of occurring and severity to indicate risk score that have adverse effect on workers' safety in their workplace based on a systematic approach. Risk priority number can also be determined by severity, detention and occurrence data. These two methods will help the industry to understand immediate concerns and prevent injuries from these accidents in that section. [ABSTRACT FROM AUTHOR]

In this work, the demand pattern of readymade garments of a knit garments factory in Bangladesh was studied and factors influencing the demand pattern were identified. An accurate sales forecast is a prerequisite of achieving an accurate and effective supply plan of complete garments. A Fuzzy Inference System based algorithm was developed to predict the sales of garments according to the sales influencing factors. The developed algorithm is mainly a quantitative method of forecasting but also takes into account some qualitative issues. The developed model was compared with the actual total sales found by traditional seasonal forecast with trend adjustment. The seasonal factors for the two cyclic demand patterns, January -- June, and July - December of each year were calculated and the Linear Regression trend was followed to calculate the traditional forecasting. The developed model showed better prediction as it matches closely with the actual sales. The Root Mean squared Error (RMSE) and Mean absolute deviations (MAD) are 3.605 and 3.081 in the developed fuzzy model which is within the standard limit. Thus the obtained result showed by the Fuzzy model yields better demand prediction taking into account the inherent uncertainties and with less error and thus the efficiency of the proposed Fuzzy model was verified. [ABSTRACT FROM AUTHOR]