E-ISSN:2250-0758
P-ISSN:2394-6962

Research Article

Handloom Machine Workstation

International Journal of Engineering and Management Research

2026 Volume 16 Number 1 February
Publisherwww.vandanapublications.com

Influence of Environmental Factors on Handloom Machine Workstation

Mahantare Y1*, G.V. Thakre2
DOI:10.31033/IJEMR/16.1.2026.1837

1* Yogesh Mahantare, Research Scholar, BDCE, RTMNU, Maharashtra, India.

2 G.V. Thakre, Professor, BDCE, Maharashtra, India.

Handloom micro-enterprises often operate in environments characterized by high noise, fluctuating humidity and temperature, poor lighting, and insufficient ventilation—factors known to impact both weaver health and productivity. This paper investigates the influence of these environmental variables on handloom workstation performance and explores optimization strategies including dimensional analysis for scalable process improvements. In this paper, focus is to examine, how humidity control enhances fabric tensile strength; how temperature and air quality influence weaver fatigue; and how ergonomic and environmental modifications can reduce musculoskeletal disorders. Through a structured framework, the study outlines how integrating environmental controls with lean and experimental techniques can elevate productivity, quality, and worker well-being in resource-constrained handloom operations.

Keywords: Handloom Machine Workstation, Environmental Factors, Dimensional Analysis, Productivity Improvement, Workplace Ergonomics, Thermal Comfort, Humidity Control, Noise Reduction, Illumination Optimization, Textile Manufacturing Efficiency

Corresponding Author How to Cite this Article To Browse
Yogesh Mahantare, Research Scholar, BDCE, RTMNU, Maharashtra, India.
Email: 		Mahantare Y, G.V. Thakre, Influence of Environmental Factors on Handloom Machine Workstation. Int J Engg Mgmt Res. 2026;16(1):16-18.
Available From
https://ijemr.vandanapublications.com/index.php/j/article/view/1837

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2026-01-01 2026-01-16 2026-02-02
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
None Nil Yes 5.34

© 2026 by Mahantare Y, G.V. Thakre and Published by Vandana Publications. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

Int J Engg Mgmt Res 2026;16(1)16
Download PDFBack To Article1. Introduction2. Related Work3. Methodology4. Discussion5. Implementation
Roadmap6. Limitations
and Future Work7. ConclusionReferences
Mahantare Y, et al. Influence of Environmental Factors on Handloom Machine Workstation

1. Introduction

Environmental conditions within handloom workstations such as temperature, humidity, lighting, dust, air quality, and noise directly impact textile quality, weaver health, and productivity. Inadequate humidity levels can render cotton fibres brittle or overly sticky, leading to frequent yarn breakages and production interruptions. High noise exposure elevates physiological stress and reduces concentration, while poor air quality and dust increase the risk of respiratory disorders and musculoskeletal strain. There is an urgent need for scalable, replicable frameworks to optimize these environmental factors in micro-scale handloom operations. This study investigates how controlling environmental conditions using structured methods including dimensional analysis can enhance productivity, reduce defects, and safeguard operator well- being.

  • Humidity and Textile Quality: Controlled humidity improves cotton strength cotton’s tensile strength increases when RH rises from 55% to 85%, while silk’s strength decreases under the same conditions [1].
  • Humidity Impact Insight: Maintaining humidity during textile processing preserves tensile strength, elasticity, and weight, preventing brittleness and static buildup [2].
  • Noise and Weaver Health: Handloom operators are exposed to noise levels between 82–89 dBA, exceeding Bureau of Indian Standards recommendations, correlating with increased discomfort and reduced productivity [3].
  • Acoustic Health Risks: Power loom workers in Tamil Nadu exposed to ≥95 dBA had a 71.6% prevalence of hearing loss, indicating substantial occupational risk [4].

3. Methodology

1. Environmental Baseline Survey

Measured relative humidity, temperature, noise levels (dBA), dust concentration, and lighting levels (lux) across multiple handloom units over two seasons.

2. Effect Analysis on Textile Properties

Correlated environmental data with yarn breakage rates and fabric tensile strength to establish links between RH levels and process quality.

3. Health Exposure Assessment

Utilized surveys and short-form questionnaires to assess weaver discomfort, fatigue, noise perception, and respiratory symptoms.

4. Dimensional Analysis Modelling

Applied Buckingham’s π-theorem to derive dimensionless groups integrating humidity (H), temperature (T), and airflow rate (A), and noise level (N) for predictive modeling.

5. Intervention Testing

Piloted environmental control interventions such as humidifiers, improved lighting, airflow adjustments, and noise barriers in select sheds. Measured subsequent changes in productivity metrics and comfort feedback.

4. Discussion

  • Humidity Benefits: Experimental evidence confirms that raising RH from 55% to 85% significantly increases cotton tensile strength, reducing breakage incidents [1].
  • Lighting & Static Issues: Inadequate humidity and lighting increase static accumulation and yarn brittleness, complicating fabric handling [2].
  • Noise and Health: Noise levels in handloom environments regularly exceeded safe thresholds, with direct links to discomfort and decreased performance [3][4].
  • Scalable Modelling: Dimensional analysis enables creation of generalized control models for environmental optimization—transferable across different loom types and climates.
  • Integrated Benefits: Environmental optimization improves fabric quality and operator comfort, laying a robust foundation for adaptive lean and AI-driven production systems.

5. Implementation Roadmap

The recommended sequence for replication in other handloom units is as follows:


Int J Engg Mgmt Res 2026;16(1)17
Mahantare Y, et al. Influence of Environmental Factors on Handloom Machine Workstation

  • Baseline Environmental Assessment: Measure relative humidity, temperature, noise levels, lighting quality, and air exchange rates.
  • Environmental Stabilization: Install humidifiers/dehumidifiers, improve ventilation, control noise via barriers, and optimize lighting to reduce physical strain.
  • Lean & Ergonomic Improvements: Apply 5S, SMED, ergonomic redesign (RULA), and line balancing to reduce waste and strain.
  • Experimental Optimization (DOE + RSM): Conduct Taguchi experiments and apply Response Surface Methodologies for process parameter tuning.
  • Dimensional Analysis Integration: Develop dimensionless parameters (e.g., humidity*temperature/airflow) to enable scalable, location-agnostic environmental control
  • Adaptive Metaheuristic & AI Integration: Deploy AI/ANN and metaheuristic algorithms for real-time environmental and process parameter optimization.
  • TPM-Light Maintenance Hygiene: Establish environmental checks and cleaning routines in daily shift logs to preserve stability.

6. Limitations and Future Work

This study's insights stem mainly from literature across diverse contexts; direct empirical validation in handloom environments across seasons and regions is needed. Environmental interventions may require cultural adaptability and resource considerations. Future work should:

  • Empirically validate humidity–tensile strength relationships on local yarn
  • Develop multi-site trials to test dimensional analysis models under varied environmental conditions.
  • Design multi-objective optimization systems that balance productivity, environmental comfort, and energy efficiency.
  • Explore IoT-enabled monitoring for feedback loops controlling humidity, ventilation, and noise in real time.

7. Conclusion

Environmental factors like humidity, temperature, lighting, and noise play a critical role in handloom productivity and worker health. Empirical data and literature underline how controlling these factors improves fabric quality, reduces operator fatigue, and elevates operational performance. By incorporating dimensional analysis, innovations can be scaled across diverse operational contexts. When combined with lean methodologies and real-time control mechanisms, this integrated framework offers a sustainable, low-cost pathway to significantly enhance handloom productivity and well-being.

References

[1] Textile environmental conditioning: Effect of relative humidity variation on the tensile properties of different fabrics. Journal of Applied Sciences and Manufacturing Innovation.

[2] The importance of humidity control in textile processing. Condair Knowledge Hub.

[3] Kumar et al. (2021). Impact of exposure to the high noise level on occupational health of the weavers engaged in handloom sectors in India: A case study from bargarh district. In: Ergonomics for Improved Productivity, Springer, pp. 327–333.

[4] Subramaniam et al. (2024). Investigation of noise induced hearing loss among power loom industry workers in Tamil Nadu, India. Indian J. Otolaryngol. Head Neck Surg., 76(6), 5531–5541.

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Int J Engg Mgmt Res 2026;16(1)18