3 ways artificial intelligence can improve efficiency

TOKYO: Hitachi has developed artificial intelligence (AI) technology which provides appropriate work orders.

The intelligence is gathered based on an understanding of demand fluctuation and on-site kaizen activity derived from big data accumulated daily in corporate business systems.

Following are five main features of the AI:

1. Understanding human ideas and kaizen, and translating this to work orders: Although on-site workers conduct tasks based on work orders issued by business systems analyzing big data related to work details or results, they also devise and implement new approaches and kaizen drawing from experience.

The AI automatically analyzes the outcome of these new approaches, and selects processes which produce better results and applies it to the next work order. By understanding and applying the ideas of on-site workers and their kaizen activity to work instructions on a daily basis, it is possible to create an environment where humans and AI mutually cooperate to continuously raise efficiency.

2. Automatically select appropriate data from big data and flexibly respond to demand fluctuation: When developing conventional business systems, expected busy or off-peak season related demand fluctuations are taken into consideration in the design but this has not been able to accommodate for short periods of bad weather or sudden increases in demand.

The AI automatically selects and analyzes data similar to the actual work conditions of the day from past big data on work detail, volume and weather to provide appropriate instructions in response to short period of bad weather or sudden changes in demand.

3. Quickly intake various forms of big data: Business systems accumulate big data in various alphanumeric forms including symbols, such as amount, time and product codes.

In order to analyze this data with AI, it is necessary to have a domain expert in the business task pre-analyze the data, making data analysis even more time-consuming. The AI analyzes the statistical distribution of the data, and by automatically pre-categorizing the data notation format, enables new data to be integrated quickly without assignment by a human interpreter.

As a result, it becomes possible to automatically incorporate daily kaizen by employees or demand fluctuation into the system to produce appropriate and timely work instructions.

Use case:
For instance, to verify the benefits of the AI, an on-site demonstration with a warehouse management system equipped with this technology was conducted, measuring item collection efficiency in a distribution warehouse. Comparative results of a warehouse system with and without this technology, showed an 8 percent decrease in work time based on instructions issued by the system with this technology.

In addition, Hitachi intends to apply the AI to various other areas such as finance, transport, manufacturing, healthcare, public works, and distribution.