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Social Innovation

Hitachi develops artificial intelligence capable of grasping site conditions and issuing work orders

Hitachi has developed artificial intelligence (AI) technology capable of understanding subjects such as demand fluctuations and kaizen activities in the workplace based on the big data collected daily by business systems. The technology is also capable of issuing appropriate work orders. Integrating this technology into business systems across a wide range of fields will make it possible to grasp the individual skills of on-site operators and kaizen activities, select the results that generate greater work efficiency, and incorporate these results into future work orders.

Verified improvement of approximately 8% in the business efficiency of logistics operations

In the business systems used to date, it has been difficult to incorporate factors such as the individual skills of on-site operators and kaizen activities as well as short-term unseasonable weather or sudden increases in demand, largely because such systems operate in accordance with programs designed in advance. Accordingly, Hitachi has developed artificial intelligence (AI) capable of issuing appropriate work orders through the independent selection and analysis of data closely reflecting business conditions on a given day-including the nature and volume of work and weather conditions. Such analysis incorporates big data on a wide range of related topics, including past business activities and performance. The repetition of operations reflecting these work orders on a daily basis makes it possible to strengthen business efficiency on a continuing basis. Statistical analysis of data distributions, automatic detection of data formats such as quantities, times, and product codes, and the loading of new data without human intervention enables timely work orders that automatically reflect daily efforts by operators and demand fluctuations in business systems. Field testing involving the integration of this AI technology into a logistics warehouse management system and assessments of the efficiency of collection operations have showed approximately 8% decrease in work time.

  • Release Date: September 4, 2015