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2021. 8. 18. | Time to read: 2 min
Drishti 이사회의 설립자이자 회장인 Prasad Akella박사는 기술을 사용하여 인간의 능력을 확장하는 세 번째 거대한 시장 카테고리를 만들고 있습니다. 1990년대에 프라사드는 세계 최초의 협동 로봇 (‘cobots’, 2025년까지 120억 달러의 시장이 될 것으로 예상되는 예상됨 코봇)을 개발한 제너럴 모터스 팀을 이끌었습니다. 2000년대 초, 소셜 네트워킹의 선구자인 Spoke의 공동 설립자로서, 현재 수조 달러의 가치를 가진 거대한 소셜 그래프를 구상하고 그 구축을 지원했습니다. 현재는 Drishti에서 AI 기반 생산이라는 형태로, AI의 인식력과 공장에서의 인간의 유연성을 조합하는 것에 임하고 있습니다. Prasad는 캘리포니아 마운틴 뷰에 기반을 두고 있습니다.
Each industrial revolution — from Industry 1.0 to Industry 4.0 — was driven by the creation and adoption of a new propellant that ushered in new capabilities that fundamentally changed manufacturing.
In the late 18th century, mechanical production was spurred on by the introduction of steam and water powered machines, with the creation of the power loom in 1784 — this in turn launched Industry 1.0 and birthed the use of machinery. It wouldn’t be until the 20th century, with the introduction of electricity, that manufacturing would begin to resemble its modern self, as Industry 2.0 took off and introduced assembly lines, streamlining mass production processes.
Industry 3.0 was spurred by breakthroughs in electronics, which gave rise to transistors and integrated circuits, which made way for the integration of software like ERP and other inventory tracking systems. Industry 4.0 is fueled by data, which can unlock insights into areas that prior technology was limited in impacting.
With data, manufacturers can now transform the entire product creation and delivery process—including design for quality—to lean things out. In the case of design for quality, the massive volumes of data created on the plant floor can be used by product and process designers in the design for manufacture and quality process to engineer in quality. Thereby, turning quality processes into the more appropriate verification role. For example, Drishti's solutions can provide data on every single cycle on manual assembly lines, allowing team leaders and line associates to identify deviations from standardized work based on cycle time measures. And, to study them using lean tools like A3 as most quality issues have a strong correlation to non-compliance with standardized work.
An example of the transformative potential that this measurement capability enables is the introduction of the powerful notion of A/B testing—the ability to easily make process changes on the plant floor, measure the impact of these changes, and make quick business decisions based on the learning. Not unlike ecommerce websites constantly testing product promotions, the world of manufacturing can now run kaizens all day long! True continuous improvement, empowering not just the industrial engineers but everyone—including the line associates who best know the tasks—in the plant. This reduction in testing time creates a fast feedback loop around the design and build process that results in a much better product for the buyer. .
Industry 4.0, the coalescence of all the past industrial revolutions, is fueled by new data sets and the ability to analyze those data sets to pull insights at the systems level. Technology like Drishti, which uses AI and computer vision to produce data on manual operations, provides visibility into the entire manufacturing ecosystem and is able to feed into other technological innovations, such as ERP and QMS systems, and elevate them to a more efficient level.
I chatted about this and a lot more with Lisa Meadows, senior site SQM at Volvo and Dirk Dusharme, editor-in-chief of Quality Digest, on a recent webinar. For more content of this nature, check out the full stream.
