April | 2017
A recent IDC report said that the market for cognitive/AI solutions will experience a compound annual growth rate of 55.1% over 2016-2020i. The report said that manufacturing presented one of the handfuls of industries with significant near-term opportunities to leverage AI. The reason is relatively simple: Manufacturing has a wealth of unstructured data that could be harnessed to improve quality, optimizing supply chains and create better products and processes.
A global study done by The Economist Intelligence Unit (EIU) sponsored by Wipro called Artificial intelligence in the real world: The business case takes shapefound that manufacturing executives believe that AI will, over the next 5 years, have the biggest impact on product development (33%), followed by production/ assembly (29%) and Inventory management (27%). The study, which surveyed executives from financial services, manufacturing, retailing, health and life sciences, and used in-depth interviews with AI experts, was particularly revealing. In the manufacturing industry 48% respondents said that AI would threaten incumbents. By comparison, 37% in financial services, 28% in healthcare and 30% in retail felt that AI would threaten incumbents.
Manufacturing, starting with Henri Ford, has always tried to automate production. But the efforts have largely been limited to defined and controlled environments where robots were "programmed" to act in a highly precise manner. Now, with recent progress in AI using techniques such as Cognitive Computing, Deep Learning, Machine Vision and Natural Language Processing, this is changing. Instead of using programming, AI techniques use demonstration to "teach" and create flexible systems that observe, learn and think like humansii, making it possible to integrate AI across production chains.
This could imply that manufacturers must step up their efforts to integrate AI into business. In which areas of manufacturing is AI likely to be deployed? Per Vegard Nerseth, managing director of the robotics business unit at ABB, told the EIU researchers that manufacturers will likely deploy it first in front-office functions. The reason is the need for absolute certainty of reliability. "When it comes to high-volume manufacturing, no management team would risk [deploying AI] before they are 100% sure of a system's reliability," said Nerseth. "They need to be certain of very high levels of uptime. An outage of just 15 minutes could be devastating for large producers." Although it may be early days to put AI in control of shop floors, clearly nothing must stop manufacturers from using AI in front office systems.
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