Nomenclature
Chapter 7: Conclusion, achievement, recommendations and scope for future work
3.1 Introduction
The previous chapter presented the research gap, objectives of this study and methodology followed during this study. Based on the research gap, the primary goal of this research work is enunciated as to redesign the TPW. As mentioned in the research gap, local people’s anthropometric data needs to be incorporated in such design process such that ergonomic design is possible. The paucity of local people's anthropometric data was a significant hurdle.
To tackle the issue, anthropometric data are collected from the target users. In this chapter, anthropometric data collection and analysis for its utility in design modification have been presented.
3.1.1 Importance of anthropometric data in designing new product
Work-related musculoskeletal disorders arise frequently in various occupational settings and are prevalent worldwide (Trevelyan and Haslam, 2001; Banerjee and Goswami, 2019;
Stiernstrom, et al., 1998; Singh and Arora, 2010; Ghaderi, et al., 2014; Huysamen et al., 2018;
Feyzi, et al., 2019; Candan, et al., 2019). Improper working posture and incompatibility between workers’ anthropometric characteristics and the dimensions of the tools/machinery employed are some of the main reasons for the emergence of such problems (Iseria and Arslan, 2009; Botha and Bridger, 1998; Dewangan et al., 2008). Ergonomics is a multidisciplinary science that helps in optimizing the relationships existing among man, machine, and the environment. It helps to improve productivity, efficiency, safety, and comfort (Pheasant, 1998;
Khadem and Islam, 2014). Although serious attention is necessary to this aspect, ergonomic principles do not receive much attention in the developing world, especially while designing
tools and machinery for rural artisans, farmers, and weavers in their respective Nations (Jafry and O’Neil, 2000). Such negligence leads to frequent work-related injuries (Obi, 2016), operation-related difficulties (Sukadarin et al., 2014), and lower efficiency (Yadav et al., 1997), all of which need serious attention from the technology development groups. One major reason for such negligence is the paucity of relevant anthropometric data in several countries such as India, where the racial backgrounds of people vary from one state to another (Patel et al., 2016) and also within a state.
Therefore, modifying the existing workplace structure and redesigning the traditional tools/machinery employed in line with the scientific applications in relation to the fresh anthropometric data of the target-community is an alternative approach to minimize the health- related issues that arise because of these factors (Syuaib, 2015). Recent examples that relates to such developments include designing hand tools and equipment for the Indian agriculture sector (Dewangan et al., 2010), the designing of a combined harvester seat for the Iranian population (Ghaderi, et al., 2014), redesigning traditional tools that are used for rice farming (Syuaib, 2015), and workspace redesigning for the Indonesian Sundanese roof tile industries (Sutalaksana and Widyanti, 2016) etc. The application of anthropometric data to reduce work- related health problems has been recommended, especially for designing tools and machinery.
This fact has been correlated by several studies conducted previously (e.g. Norrish and Wilson, 1995; Pheasant, 1998; Bolstad et al. 2001; Barroso, 2005; Klamklay et al., 2008; Iseria and Arslan, 2009; Hartono, 2018).
3.1.2 Brief review on anthropometric study related to India
In India, previous researchers (e.g. Sen, 1964; Sen et al., 1977; Gupta et al., 1983; Gite and Yadav, 1989; Gite and Singh, 1997; Yadav et al., 1997; Victor, et al., 2002; Dewangan et al.
2005; Fernandez and Uppugonduri, 2007; Dewangan et al., 2008; Gite et al., 2009; Dewangan et al., 2010; Vyavahare and Kallurkar, 2016) have made efforts to collect anthropometric data with regard to the Indian population. Such efforts were mainly concentrated on a specific region/community or for a particular requirement (Yadav et al., 1997; Mehta et al., 2008; Patel, et al., 2016). The most extensive collection of anthropometric data in India was performed as part of the project called “All India Coordinated Research Project on Ergonomics and Safety
in Agriculture” (Patel et al., 2016). In this study, the anthropometric data of several north- eastern states of India, including Assam, are missing (Gite et al., 2009; Patel et al., 2016). In this regard, one can conclude that the available literature on anthropometric data of the Indian population is inadequate to formulate a clear idea regarding variations that exist in relation to gender and ethnicity for the designing of tools/machines (Patel et al., 2016).
A serious concern in this regard is in relation to the Indian micro, small, and medium enterprise (MSME) sector, especially cottage industries, which is still dependent on age-old traditional tools and methods. Due to the slogging associated with these systems, work-related disorders and health issues have been extensively reported in the sector (Nag and Nag, 2007;
Unnikrishnan, et al., 2015; Sanjog, et al., 2019). The sector needs urgent intervention of ergonomics to improve the efficiency, safety, and comfort of the artisans associated with it.
Thus, context-specific design intervention for these hand tools and traditional workplaces needs the inputs from newly conducted anthropometric studies that deal with target-users (Victor et al., 2002; Mugisa, et al., 2016). As mentioned above, the major hindrance for such intervention is the paucity of context-specific anthropometric data.
In a previous study, Dewangan et al., 2005 conducted a survey among male farmers belonging to one of the seven north-eastern states of India, with two districts of Assam also being included in the study. Thirty-three anthropometric dimensions were collected from the people belonging to these seven states, which are summarized in the study. Patel et al., 2016 collected anthropometric data of the male agriculture workers in the Kamrup district of Assam. Data were obtained randomly from the selected villages of the district. The district is inhabited by both ethnic people and those who have immigrated from outside the state. Because the anthropometric data vary from one region to another, from one ethnic group to another, or from one climatic condition to another (Chapanis, 1974; Sengupta, 1996), special care should be taken when considering such data for a specific group of people. Assam is inhabited by various ethnic groups with a high degree of ethnic diversity. Hence, characterization of the Assamese population into a particular race is inaccurate. In such a situation, an anthropometric study involving a mixed population may not give a true representation of the anthropometric characteristics of the state. Moreover, no relevant study has reported collecting anthropometric data from the female population in the state.
The female workforce plays a significant role in the rural economy of Assam. Knowledge related to the anthropometry of the female population is crucial for designing the tools/machinery used in the state. The existing anthropometric data are primarily concerned with people associated with agricultural activities. However, no serious attention has been given to the collection of the anthropometry data of people primarily associated with non-farm activities. Thus, a need was felt for a detailed investigation of the anthropometric data of the state considering the gender and ethnic diversity of Assam.
In view of the above, the anthropometric data of five communities/tribes of Assam, viz., Boro, Garo, Hira, Karbi, and Rabha are collected and summarized. Based on previous research findings, viz., Lin et al., 2004; Dewangan et al., 2005; İşeri and Arslan, 2009; Sadeghi et al., 2015; Widyanti et al., 2015, an hypothesis enunciated for the study is that there exists a significant variation of the anthropometric dimension of the tribes/communities across genders and across ethnicities within the same gender. To examine whether the stated hypothesis is true, statistical t-test has been performed. People associated with non-farm activities, mainly people in the handicraft industries are considered for collection of the anthropometric data.
The descriptive statistical values of the anthropometric dimensions have been estimated.