使用ema软件套件的数字化生产计划和人工模拟手动和混合工作流程

M. Spitzhirn, Sascha Ullman, Sebastian Bauer, L. Fritzsche
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引用次数: 6

摘要

对于规划和设计生产和工作系统,考虑工厂规划和工作场所设计两个层面的整体方法是必要的。目前,独立的数字化工具主要用于工厂的设计和工作系统的详细规划。这导致工人在生产计划过程中被认为不充分或太晚。其结果可能是耗时且昂贵的重新规划,以解决现有生产和工作流程中的问题。以洗衣机装配为例,提出了一种迭代方法,用于工厂和工作场所层面的综合数字化规划。使用ema软件套件对装配线进行整体设计,包括ema工厂设计器(emaPD)和ema工作设计器(emaWD)。在案例研究中,emaPD通过考虑物料流、生产时间和生产成本,优化生产要素,如作业资源、布局和物流。这些结果应用于工作站级别的emaWD的详细规划和设计,emaWD使用基于客观任务描述的自启动运动生成算法方法。根据生产时间估计(MTM-UAS)、人体工程学风险评估(EAWS、NIOSH、到达和视力分析)以及工人的能力(年龄、人体测量),对生成的模拟进行检查和优化。因此,可以规划一个具有优化物料流的高效工厂,同时最大限度地降低制造成本和生产时间,同时符合空间规范和人体工程学。机器人作为混合工作站接管对人体工程学不利的过程,除其他外,还可以改善人体工程学。结合工厂(emaPD)和工作场所设计(emaWD)的数字规划方法也可以实现经济和符合人体工程学的生产的早期,协调,有效的规划。
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Digital production planning and human simulation of manual and hybrid work processes using the ema Software Suite
For planning and designing production and work systems, a holistic approach is necessary that considers both levels of factory planning and workplace design. Currently, separate digital tools are mostly used for the design of factories and the detailed planning of work systems. That leads to workers being considered inadequately or too late in the planning process of production. The consequence can be a time-consuming and costly replanning to solve problems in existing production and work processes. Using the example of an assembly of washing machines, an iterative approach is presented for a combined digital planning on factory and workplace level. A holistic design of the assembly line is carried out using the ema Software Suite, consisting of the ema Plant Designer (emaPD) and ema Work Designer (emaWD). In the case study, emaPD is used to optimize production elements such as operating resources, layout, and logistics by considering the material flow, throughput times, and production costs. These results are applied for detailed planning and design at the workstation level with emaWD, which uses an algorithmic approach for self-initiated motion generation based on objective task descriptions. The generated simulations are examined and optimized based on production time estimation (MTM-UAS) and ergonomic risk assessments (EAWS, NIOSH, reach and vision analysis) as well as workers’ abilities (age, anthropometry). As a result, an efficient factory with an optimized material flow could be planned while minimizing the manufacturing costs and throughput times while complying with the space specifications and ergonomics. The takeover of ergonomically unfavorable processes by robots as hybrid workstations enables, among other things, an improvement in ergonomics. The digital planning approach of combined factory (emaPD) and workplace design (emaWD) also enable early, coordinated, efficient planning of economical and ergonomic production.
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