Abstract
Our study rigorously compared the efficacy of Methods-Time Measurement (MTM 1) and Maynard Operation Sequence Technique (MOST) against actual production times to identify the most accurate and efficient time management frameworks for manufacturing processes. We aimed to discern which method better predicts job completion times in a real-world setting, using a case study that included both manual and robotic welding in the assembly of a truck body part, the tipper tailgate. We discovered notable discrepancies between the predetermined time systems and actual observations, particularly in manual welding tasks. These differences highlighted the complexity of manual tasks, which involve intricate movements not fully accounted for by the predetermined systems. MOST emerged as more effective than MTM 1 in providing a detailed understanding of task execution times, especially in tasks that involve complex positioning. The study also delved into the comparison between the performance of skilled human welders and automated robotic systems. Our findings revealed that while robots can significantly enhance efficiency for simpler, repetitive tasks, the complex assembly work still requires the dexterity and expertise of skilled human welders. Surprisingly, in certain cases, human welders outperformed robots, underscoring the unique strengths and weaknesses of both. The analysis further demonstrated that robotic welding offers superior time efficiency and cost-effectiveness compared to manual welding, particularly as production volume increases. This efficiency translates into significant cost savings and increased production rates, making the case for integrating robotic technology into manufacturing processes compelling. Crucially, the coexistence of skilled welders with collaborative robots (cobots) brings immense benefits, merging human expertise with robotic precision and efficiency. This synergy not only optimizes production quality and speed but also mitigates the impact of skilled labor shortages. By embracing a hybrid approach to welding, manufacturers can achieve a balance between the adaptability and problem-solving skills of human welders and the consistency and productivity of robotic systems, leading to enhanced operational excellence and competitive advantage in the manufacturing sector.
Advisor
Kuldeep Agarwal
Committee Member
Shaheen Ahmed
Committee Member
Pawan Bhandari
Date of Degree
2024
Language
english
Document Type
Thesis
Degree
Master of Science (MS)
Program of Study
Manufacturing Engineering Technology
Department
Electrical and Computer Engineering and Technology
College
Science, Engineering and Technology
Recommended Citation
Suggula, Aditya. (2024). Comparative Study of Robotic And Manual Welding In A Low Volume-High Mix Manufacturing Environment: Case Study Of Tail Gate [Master’s thesis, Minnesota State University, Mankato]. Cornerstone: A Collection of Scholarly and Creative Works for Minnesota State University, Mankato. https://cornerstone.lib.mnsu.edu/etds/1430/
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