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Effects of Mechanization on Resource Productivity

Authors: Puneet Grover; Solanki, Sushil Kumar;

Effects of Mechanization on Resource Productivity

Abstract

Construction sector is one of the biggest sectors contributing to the global economy and the biggest issue that this sector faces is less than expected productivity at job sites. These variations in productivity cause the durations of the activities to extend beyond the scheduled timelines leading to cost/time overruns. This dissertation is an attempt to first review productivity and various approaches for productivity measurement for the purpose of which systematic review of the past literatures published in well-established journals with specific reference to resource productivity is carried out. Literature review along with personal interactions with industry experts is conducted to analyze the effects of mechanization on the overall productivity/output. The findings of which indicate that there are 4 levels of mechanization and with the increase in level of mechanization the productivity increases. Subsequently, the research uses accountancy-based approach to derive the productivity constants from published and industry known manual CPWD's DAR (latest version) and compares it with the secondary case study data collected which indicates that the productivity values and labour requirements derived as per DAR, 2021 are very different compared to the secondary case studies. To further confirm the hypothesis, multiple observations are made at 20 different locations, in 11 case studies of different sizes, at 3 different height levels, and 3 different mechanization levels. Labour utilization rates are also calculated to identify the overall efficiency of the labour. The data collected is then analyzed and presented in a tabular form which can be used to estimate productivity and a resource estimation sheet is formulated on excel which can help estimate the amount of labour and machinery required to achieve a particular productivity. Further the various inadequacies are identified and suggestions are made to improve the labour utilization at sites which would eventually lead to increase in productivity values.

{"references": ["1.\tY. Kumar, \"Productivity Analysis of Small Construction Projects in India,\" 2014.", "2.\tS. Rastogi, \"An approach to dynamic productivity based resource scheduling,\" 1996.", "3.\tH. M. M. J. A. B. H. Alinaitwe, \"Factors affecting the productivity of building craftsmen - studies of uganda,\" 2007.", "4.\tK. Vishwakarma, Mechanization and automation in construction, 2022.", "5.\tR. P. V. K. &. S. S. Rastogi, \"Analyzing the Impact of Challenges in Prefabricated Building Construction Supply Chains.,\" Journal of Engineering Research and Sciences, JENRS, 2022.", "6.\tS. B. R. Mistry, \"Critical Factors Affecting Labour Productivity in Construction Projects: Case Study of South Gujarat Region of India,\" 2013.", "7.\tM. S. O. A. P. A. H. K. Hammad, Ways to improve productivity in construction industry., 2011.", "8.\tA. Gupta, \"study of productivity and productivity enhancing techniques for multi-storied buildings,\" 2009.", "9.\tC. H. P. H. W. H. G. A. P. H. W. Oglesby, Productivity improvement in construction, 1989.", "10.\tF. B. J. D. Liou, \"Work Sampling Can Predict Unit Rate Productivity.,\" 1986."]}

Keywords

productivity, concreting, impact factors, mechanization, productivity improvement.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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