Hitachi, Ltd. | Integrated Report 2016

HITACHI’S AI
OPENING A NEW ERA
Hitachi AI Technology/H
Hitachi’s artificial intelligence technology, Hitachi AI
Technology/H, is generating new economic growth withAn experiment in which Hitachi-developed
AI learns to make a swing go higher. Whilelearning itself how to pump to make theversatility that makes it applicable to diverse indus-

height increase, the AI came up withtries even in a rapidly changing, unpredictable age.

techniques that a human on the swing

AI for Continuing Economic Growth

Hitachi AI Helping People Work TogetherRecent years have seen an increase and diversification of data

The major characteristic of H is its versatility. Most new technology

types and formats, thanks to the rapid spread of cloud computing,has a history of being invented first for a specific purpose, later

mobile devices, and social media, along with the development of

spreading throughout more of industry and society as it is gener-new sensor technologies to capture this data.

alized. At Hitachi, our prediction that AI will certainly reach an

In previous analyses conducted by human specialists, it waswould not have invented.

age of generalization has led us to pursue a more versatile AI

becoming increasingly difficult to test hypotheses through exhaustive

implementation from the very beginning.

sifting of this vast amount of data. As these data-driven results

H has three further characteristics.

became more inaccessible, it gave rise to social problems, such asa digital divide that was directly linked to an income divide.
In response to these changes, Hitachi developed technology(1) Human users define and input the outcome to be achieved.
(2) There is no need to define a specific method to solve theto use and apply this “big data,” and in 2012 launched a full-scale

problem or application in question.

big data analysis service. We have relationships with a wide range(3) H can be applied to existing systems.

of customers in the electric power, manufacturing, distribution,finance, transportation, and water industries, and are making

For example, when the goal of “increasing sales” is input into

efforts to link infrastructure and products using the Internet ofH, it analyzes enormous quantities of past data and “thinks” onThings (IoT) and other means. In 2016, we began providing theits own to derive the best method to achieve this. Since it can beLumada IoT platform, developed as a core for social innovation.

added to existing systems, installation costs are also kept down.

One of its basic functions is Hitachi AI Technology/H, or simply

It is still humans, however, that define the goal for H and imple-“H” hereafter.

ment the measures it recommends. Hitachi H is a system in which

Now that Hitachi’s H has been put to practical use in varioushumans and AI learn together through data to raise productivity.

industrial fields, we are building on our findings to improve thefuture, based on past data, and successfully deriving methods todeal with unknown problems.

Hitachi’s Approach to AI Systems
Monitoring ¦¥ MonitoringControl ¥¦ Control

Point 1:
Learn from data and grow while adapting tocircumstances to produce results

Existing systems
IT/equipment

Artificial intelligence
Hitachi AI Technology/H

HumansCustomers/
employees

Point 2:
Optimize the system as a whole, including its human users
23Example of AI DevelopmentVersatile Hitachi AI Technology/H can respond to a wide range of work content, and is already producing resultsin many different industrial sectors.

Versatile Technology for Application in Diverse Fields

Contributing to Energy Savings in Railway Operation

Hitachi provides a wide range of services, from construction ofWith the goal of reducing CO2 to counter global warming,

electric power facilities, railroads, and other large-scale social

improved energy efficiency is needed in railway systems in Japan

infrastructure to manufacture of general household products.

and other countries. Railway systems consume 60% to 80% of

The accumulation of business data in these diverse fields worked

their total energy during rolling stock operation, and Hitachi has

to our advantage in the development of H. With the same AI

developed rolling stock and related systems to achieve energy

software, H provides comprehensive improvement strategies forsavings. H was introduced to verify these energy-saving effects.

businesses in completely different industries. Our record to date

Railway systems collect many different types of sensor infor-includes 57 cases in 14 fields, including distribution, logistics,

mation, including through remote monitoring of rolling stockindustrial plants, finance, transportation, and manufacturing.

status. H was applied to this data to derive methods to effectively

Hitachi has since 2004 been researching and developing tech-

reduce energy consumption. After analyzing a year’s worth of

nology to objectively measure human behavior. Through ourdata, the program identified various characteristics related toanalysis of huge volumes of behavioral data, we have found thatenergy consumption from factors including speed, track gradient,

people who work in organizations featuring behavioral diversity

and operating schedule. Based on analysis of the massive data on

have high levels of happiness, and that groups with high levels of

the control of the “notch,” equivalent to the accelerator on anorganizational happiness have high productivity. In other words,

automobile, and its electric power consumption, we reduced

employees’ happiness is closely related to their organization’s

drive system power consumption by shortening the time of train

activity and should be considered to strongly affect productivity.

operation at maximum notch and lengthening the time of notch-

Hitachi has quantified this as a unique index: “organizationaloff operation. Even greater effects are predicted if operatingactivation.” In June 2016, we kicked off a demonstration experi-

procedures can be further improved.

ment using H to offer advice to 600 sales and marketing division

Future uses of H for railway systems big data are envisioned to

employees in the Hitachi Group in order to effectively increase

include applications to reduce energy consumption in the auxiliary

happiness. The aim is to raise productivity by providing the orga-circuit systems used in air-conditioned cars and door opening/

nization with fresh energy tied to increased individual happiness.

closing, and to make settings with the purpose of achieving riding

With AI, Hitachi pursues optimization of overall systems,

comfort in terms of noise and vibration. In railway maintenanceincluding the humans that operate them, and is accelerating its

and management work as well, it may be possible to use H toSocial Innovation Business.

analyze employee “happiness” and apply the findings to raising
work efficiency. In raising car utilization, H is promising for deriving
the relationship between car deterioration with age and operating
conditions, and may possibly be applied to prevention and detection of equipment failure.

Employees with name-tag-style wearable sensors, which collect data on their behavior
when interacting with others for analysis by H.

24

Hitachi, Ltd. | Integrated Report 2016

Use in the Field of Finance for a FinTech Age

AI to Link Manufacturing-Sector Facilities

Financial services have expanded together with the progress in IT.

Use of IoT is progressing in the manufacturing sector. In Western

FinTech, a coined term combining the words “finance” andcountries, government-led efforts are under way to construct“technology,” refers to the new financial services that haveand standardize new industrial “ecosystems” integrating theappeared in recent years, bringing together finance and IT tomanufacturing and IT industries.

improve user convenience. Typical examples of FinTech are services

Hitachi has provided control and production management

using the Internet to move capital beyond the scope of traditional

systems to the steel, automobile, pharmaceutical, and various otherservices and business frameworks, as well as crowdfunding, whichindustries, and has a proven record in constructing large-scaleprocures capital from multiple individuals using social networks.

control systems in fields from energy and transportation to water

Hitachi has focused on AI in the financial industry as well,and sewage. Building on this experience, we produce value byconducting a joint experiment with The Bank of Tokyo-Mitsubishi

linking various systems to the manufacturing industry and social

UFJ that puts human behavior measurement and analysis tools toinfrastructure. We have proposed the concept of “symbioticuse in improving quality and supporting work style reforms. Up

autonomous decentralization” to promote new growth.

to now it has been possible to acquire behavioral data on several

Previously, optimization was limited in scope to analyses onhundred people in units of seconds, but specialist analysis was

the individual system level and site improvements based on thoserequired to judge those people’s level of contribution to organiza-analyses. Linking factories by symbiotic autonomous decentral-tional activation, and both time and cost were issues. Hitachiization, however, makes it possible to carry out optimization overdeveloped name-tag-style wearable sensors to measure people’s

multiple systems and create new value chains.

behavior when in groups. H then analyzed the behavioral data

Other beneficial effects of linking factories include improved

obtained from those sensors, automatically and efficiently produc-energy productivity and coordination with supply chain manage-

ing recommendations on ways of working to raise productivity.

ment across global sites. An impact is also expected in business

The experiment drew on behavioral data from 40 employees

continuity plan (BCP) responses to cyber attacks and other factorycollected over three weeks. It found, for example, that one

operation risks.

employee showed a high level of organizational activation on a

In some manufacturing sites, H has been used to analyze vast

day when there were frequent short conversations, including

amounts of data collected by control systems on manufacturinggreeting others and making brief reports. This demonstrated thatequipment, manufacturing processes, and product quality. We have

while the productivity of specific individuals may decrease withbegun to analyze the relation between equipment or processes

repeated conversations, the productivity of the organizationand quality or yield rate. H can derive statistical characteristics

overall can rise. AI analyses that quantify individual contributions

through big data analysis that would be nearly impossible forto the organization as a whole can be useful for optimizing

humans to perform. In manufacturing sites where conditions areservices and working styles.

inconsistent, due to factors like manufacturing processes thatchange daily and equipment wear and deterioration, H is useful
in defining operating conditions that are appropriate to thechanges and obtaining new hints for improvements.

Application Examples of Hitachi AI Technology/H
Just one AI software package has enabled versatile improvement in fields from distribution, logistics, and industrial plants tofinance, transportation, and manufacturing
Distribution

Logistics

Detailed analysis of customer and employee behavior identified “high sensitivityspots” to station employees to boost average sales per customer.

Analysis of daily shipment work results led to work instruction improvement
plans for the following day; these were reflected in the picking list
(work instruction chart).

Sales per customer up 15%

Productivity up with 8% reduction in work hours

Call centers

Desalinization plants

Data analysis on employee behavior found relationship between verbal support fromsuperiors and order receipt rate. H identified employees needing priority attention.

Examination of operating history data helped reduce clogging of the reverse
osmosis (RO) membrane, a factor impacting uptime for seawater filtration units.

Order receipt rate up 27%

Operating cost: 3.6% reduction25