Improving Standard Work Time Using MOST for Sustainable Automotive Welding Operations

This study addresses productivity and sustainability challenges in automotive welding-part production, where inefficient operator motion and lack of standardized work contribute to production shortfalls and resource waste. The objective is to improve standard work time and operational efficiency while supporting environmental sustainability in manufacturing systems. An applied industrial engineering approach was used, integrating time study, Pareto analysis, and the Maynard Operation Sequence Technique (MOST) to analyze and redesign work processes. Data were collected through observation, time measurements, and production records across key components. Pareto analysis identified priority areas, while MOST decomposed tasks into motion elements to quantify non-value-added activities. The results show reduced standard time and increased output, with Radiator and Backdoor achieving targets and other components improving significantly. Inefficiencies were mainly caused by excessive material handling, poor layout, and non-standardized work. Eliminating these factors enhanced productivity and reduced unnecessary motion and energy use. The findings demonstrate that MOST effectively supports both operational performance and sustainable manufacturing by reducing waste, improving process stability, and optimizing resource utilization in automotive production systems.本研究聚焦汽车焊接零部件生产领域的生产效率与可持续发展难题，作业人员动作低效、作业标准化不足是导致产能缺口与资源浪费的重要诱因。本研究的目标在于优化标准作业时长、提升运营效率，同时助力制造系统实现环境可持续发展。本研究采用应用工业工程方法，整合时间研究、帕累托分析与梅纳德操作序列技术（Maynard Operation Sequence Technique, MOST）对作业流程开展分析与重构工作。研究通过实地观察、时间测量以及关键零部件的生产记录完成数据采集。帕累托分析明确了优先级改进领域，而梅纳德操作序列技术则将作业任务拆解为动作单元，以量化非增值活动。研究结果显示，标准作业时长得以缩短、产能显著提升：散热器（Radiator）与后车门（Backdoor）组件顺利达成改进目标，其余零部件亦实现大幅优化。产能低效的主要诱因包括物料搬运冗余、车间布局不合理以及作业标准化缺失。消除上述问题后，生产效率得以提升，不必要的动作与能源消耗均得到有效削减。研究结果表明，梅纳德操作序列技术可通过减少浪费、提升流程稳定性及优化资源利用率，有效赋能汽车生产系统的运营绩效与可持续制造发展。