Analysis Solution to Improve Fault Detection on Mechanical Assembly Production Lines
Analysis Solution to Improve Fault Detection on Mechanical Assembly Production Lines
批准号:
10073325
负责人:
金额:
$1.15万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
已结题
起止时间:
2023 至 --
中文摘要
**Helical Technology Ltd * 开发一种经济实惠、易于培训的视觉故障检测系统,以便在多条产品装配线上轻松部署。*挑战 **Helical Technology是一家总部位于英国西北部的家族式制造企业,从50多年前的弹簧制造商,发展成为包括阀门旋转器、执行器和阀门在内的多种专业机械产品的全球供应商。Helical在英国的两个生产基地内的许多生产线需要在给定的一天内生产各种产品,许多装配过程依赖于零部件的精确定位,以避免故障和代价高昂的质量问题。历史上,质量通常通过对零部件进行手动检查来保证,这既耗时又容易出错。在某些情况下,已经在生产线上部署了商用视觉系统,以提高产量和检查质量,但由于购买和重新配置这些系统的固有成本,这些系统在整个生产线上的使用受到限制,而这往往需要外包给第三方。解决方案 ** 在注意到机器学习和人工智能领域的最新进展后,一位螺旋工程师开始尝试使用开源代码来教授机器算法检测简化的构建错误。在取得初步成功后,我们认识到需要更多的外部专业知识和资源来生产一个完整的检测系统并进一步发展这一想法。Helical Technology寻求与STFC Hartree研究所在A4I资助的项目上建立合作伙伴关系,该项目导致了一种新颖的易于培训的分析软件方法的开发和供应,以及第一个演示单元的生产和部署。影响 ** 在螺旋生产线上部署演示系统后,立即消除了人工目视检查操作,提高了生产线的生产率和输出质量。生产线操作人员被重新部署到其他地方,从事生产率更高、负担更轻的任务。公司内部的A4I项目,并受到员工的好评,促使更多类似的项目在公司周围诞生。通过合作A4I项目,参与的Helical员工获得了技能提升,能够重新校准内部设备,开始新的项目,并以其专业知识为其他企业提供意见。透过向英国制造业广泛宣传此计划,其他同类的制造业中小企业亦会参与类似的计划,以提高竞争力。
英文摘要
**Helical Technology Ltd****Generating an affordable, easily-trainable, vision fault-detection system for easy deployment across multiple product assembly lines.****Challenge**Helical Technology is a family-owned manufacturing business based in the North-West which from establishment over 50 years ago as a spring manufacturer, has grown into a global supplier of several specialised mechanical products including valve rotators, actuators and valves.Many production lines within Helical's two UK sites are required to produce a varied range of products in a given day, and many assembly processes rely on precise positioning of component parts to avoid faults and costly quality issues.Historically, quality was often assured by conducting a manual over-check of parts, which was both time consuming and prone to error. In some cases, commercially available vision systems had been deployed on lines to improve throughput and checking quality, but their use across the production line had been limited due to the inherent costs of purchasing and then reconfiguring such systems, which often required outsourcing to third parties.**Solution**Having noted recent advancements in the fields of machine learning an artificial intelligence, a Helical Engineer began to experiment with open-source codes to teach a machine algorithm detect a simplified build error. After gaining some initial successes, it was recognised that further external expertise and resource was needed to produce a full inspection system and develop this idea further.Helical Technology sought partnership with STFC Hartree Institute on an A4I funded project, which led to the development and supply of a novel easily-trainable analysis software method, and the production and deployment of the first demonstrator unit.**Impact**The deployment of the demonstrator system on a Helical production line immediately led to the elimination of the human visual checking operation, which saw increased line productivity and quality of output.Instead of being replaced by a machine, line operatives were redeployed onto more productive and less onerous tasks elsewhere.The demonstrator unit served as a pilot "Industry 4.0" project within the business and was well received by employees, prompting further similar projects to be birthed around the business.Through the collaborative A4I project, Helical employees involved were upskilled in empowered to re-calibrate the unit in house, start new projects, and advise others with their expertise.Through publicity of this project to the wider UK manufacturing community, other similar manufacturing SMEs were prompted to undertake similar projects to increase their competitiveness.
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项目类别:外国学者研究基金项目
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批准年份:2024
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负责人:Noshaba Aziz
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依托单位: