On August 28th, Japanese beverage giant Kirin and food manufacturer Ajinomoto announced plans to integrate artificial intelligence (AI) into their production processes. This move aims to replace traditional reliance on skilled artisans, particularly in areas like fermentation and flavor management. By leveraging AI, both companies hope to accelerate product development cycles while simultaneously training younger staff more effectively.
Kirin Beer has partnered with Mitsubishi Research Institute to implement AI within its brewing operations. Once the ideal taste, aroma, color, and alcohol levels are established during testing phases, AI algorithms will determine optimal ingredient combinations including raw materials and precise temperatures. This shift marks a significant evolution in an industry historically dominated by experienced brewers who typically required over a decade to fully master their craft. With access to two decades' worth of historical data, Kirin expects AI systems to identify superior brewing techniques far quicker than human intuition alone could achieve. Implementation is set for 2017, coinciding with broader industry efforts towards restructuring amidst increasingly diverse consumer tastes. Kirin believes embracing AI will not only enhance efficiency but also ensure continued market leadership through innovative offerings.
Ajinomoto, known globally for its umami-rich seasonings, intends to apply similar principles to optimize fermentation processes at facilities producing amino acids. Their goal is to achieve fully automated operations by 2019 by quantifying key parameters necessary for maximum productivity. Furthermore, they aim to establish robust digital infrastructures capable of sharing valuable insights across borders, thereby boosting global competitiveness. While this approach remains somewhat novel within certain sectors of manufacturing, other Japanese enterprises like Renesas Electronics and Kobe Steel have already begun exploring analogous applications—Renesas utilizes AI for defect detection while Kobe Steel employs it for managing blast furnace temperatures.
This trend underscores how digitizing tacit knowledge held by veteran professionals can dramatically improve knowledge transfer efficiencies. As Kirin noted, “AI holds promise in uncovering more efficient methodologies,†reflecting optimism regarding technological succession strategies. Across various industries, there’s growing recognition that integrating advanced technologies isn't just about cutting costs—it’s also about fostering innovation while preserving critical expertise for future generations.
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