Wearable Electronics & Big Data = High Volume, High Mix Smt!

With all the excitement around IoT (Internet of Things), big data and cognitive computing the impact of wearable electronics on the manufacturing environment frequently gets lost in the noise. However, the capability and capacity to serve the needs driven by these trends falls on the shoulders of the electronics industry and in particular SMT assembly. This paper explores the seemingly conflicting requirements of achieving low cost while meeting the high volume, high mix product requirements of this brave new world of electronics systems. Software tools applied to the world of integrated circuits, e.g. field programmable gate arrays, soft radios, etc. provide the flexibility demanded in the design of smart phones, embedded controllers, and specialty sensors. Drawing on these experiences SMT assemblers can serve the burgeoning world of wearable electronics and tailor individual products to specific applications and environments using rapid change approaches driven by quantitative and qualitative analysis of large data sets that define the market expectations. The authors delve into specific tools being developed in Japan, Germany and the USA that facilitate these approaches while outlining specific changes demanded of the supply chain in order to meet the high mix needs of customers at low cost. INTRODUCTION The era of wearable electronics began quietly more than a decade ago with the advent of pedometers to passively monitor walking activity levels and rapidly progressed to today’s more sophisticated systems that monitor heart rates, blood pressure and even such things as sweat composition, glucose levels and other body parameters. Even more capable systems incorporate blood sugar sensors & insulin pumps, digitalis injectors or defibrillator activation for smart fabric vests. Only the imagination constrains the potential for wearable devices, particularly in the era of the internet of things where these devices produce incredible databases of information (big data) and interact with cognitive computing systems to improve the quality of life for everyone. And smart textiles continue to expand the possibilities. Figure 1. Medtronic wearable blood sugar sensor/insulin pump Similar to many areas today driven by big data analysis, wearable electronics offers the potential to collect huge levels of anonymous data that can be analyzed to define specific solutions to many challenges in the areas of health, workplace safety and simple comfort. However once achieved the implementation of these solutions creates rigorous demands on manufacturing infrastructure with respect to cost management, turn time and inventory management as examples. Manufacturing Challenges & Solutions Traditional manufacturing philosophy views markets from one of two perspectives; low volume/high mix or high volume/low mix. Low volume/high mix products generally drive higher costs, longer lead times and higher inventory (primarily of components and subsystems). On the other hand, high volume/low mix products generally result in lower costs, shorter lead times and reduced inventory (of components and subsystems). Of course, these generalities do not apply universally but rather indicate the usual expectations. Proceedings of SMTA International, Sep. 27 Oct. 1, 2015, Rosemont, IL Page 231 As originally published in the SMTA Proceedings.