On-site usage-data drives industrial robot design improvement

Industrial robots working as a kind of intelligent but standard equipment on manufacturing sites are outlined to be with more light-weight, more flexibility, and lower cost but higher performance in the future. Diversified products to meet customer´s expectation better and standardized product for easy management and manufacturing are always two main issues in the concept design phase. This paper looks to better odds by using big data to pinpoint customer needs and tailor new industrial robot products. To implement this work, a cycle-pool composed of amount of robot cycles collected from customer sites is established. The information extracted from cycles is illustrated as knowledge patterns and rules on a product portfolio in order to propose possible suggestions and solutions for new product development.