Showing posts with label Big Data. Show all posts
Showing posts with label Big Data. Show all posts

Friday, November 6, 2020

How far is the future blueprint of intelligent manufacturing from us?

 Smart manufacturing is not a far-reaching imagination, the digital factory has already arrived. Who brought this change, and where will it go?

China's manufacturing industry is in the throes of transformation.

Over the past 40 years of reform and opening up, China's economy has experienced sustained and rapid growth. The fundamental reason behind it is that it initially established a set of manufacturing development strategies that fit my country's national conditions, and thus became a veritable "world factory". 

Nowadays, China's manufacturing industry is facing multiple challenges. With the changes in the population structure, the labor cost advantage that has been relied on for development has been gradually lost, causing labor-intensive manufacturing to flow to Southeast Asia and other countries. 

At the same time, a new round of industrial revolution has been set off worldwide, and some major advanced manufacturing countries have introduced national strategies for manufacturing, such as German Industry 4.0 and the US Industrial Internet.

In this context, whether it is from the national strategy or the enterprise's own survival and development needs, the transformation and upgrading of the manufacturing industry cannot be delayed.

01  Misunderstandings and Challenges of Intelligent Manufacturing 

The ultimate goal of intelligent manufacturing is to integrate industrial systems with information systems, and to promote further improvements in industrial efficiency and production capacity through a data-driven approach. 

Judging from the demand for reforms of more than 350,000¹ manufacturing enterprises in China, China's smart manufacturing is a blue ocean market with great potential.

During the period, foreign companies such as Hitachi have also been attracted to participate in the transformation and upgrading of China's manufacturing industry, providing Chinese companies with valuable experience and advanced technology and equipment. 

Of course, the complexity of the manufacturing industry is destined to be extremely long, and intelligent transformation is not an easy task. 

In fact, there is an obvious misunderstanding in the current manufacturing industry, thinking that as long as the smart manufacturing solution is randomly applied to the traditional factory, the transformation and upgrading will be completed.

At the same time, many smart manufacturing solution providers lack industry experience and lack sufficient understanding of their customers' business, and the upgrade effect is not ideal.

It should be understood that the pain points and difficulties of intelligent manufacturing transformation and upgrading for any industry or company are different, so they will vary from industry to company.

In this process, a greater challenge is the increasing demand for large-scale personalized customization. With economic development, the market has gradually shifted from a seller's market to a buyer-led market.

 This small-quantity personalized customization model is becoming more and more popular, and customers have more diversified requirements for product customization.

 Looking at the entire manufacturing industry, any factory definitely likes mass production at one time, and the high-frequency and large-scale personalized customization mode is often difficult to control in terms of cost, quality and efficiency.

 This undoubtedly brings a huge challenge to the traditional mass production model. All manufacturing industries face huge pains, either upgrading on demand or waiting to be ruthlessly eliminated.

02How  to build a "factory of the future"?

Thus, flexible manufacturing has entered the stage of history.

With a flexible production model, manufacturing companies can better grasp the complex and changeable market, which means that traditional factories must carry out in-depth transformation of their own production links.

Traditional manufacturing is a rigid manufacturing assembly line, that is, through a high degree of standardization of production equipment and manufacturing processes, the assembly line system can achieve mass production of a single product while maintaining quality.

The problem with rigid manufacturing is that manufacturing companies actually bear most of the pre-investigation, huge development costs, and market prediction risks.

In contrast to rigid manufacturing, flexible manufacturing is a new manufacturing model that is created to meet the needs of customization. It can be manufactured and scheduled flexibly, and manufacturing companies can realize instant feedback on the customization needs of users.

With the advancement of industrial technology and information technology, the vision of the smart factory will eventually shine into reality. A typical feature of smart factories is flexible manufacturing, where factories are more flexible, more efficient, and lower in cost.

For example, Okuma Co., Ltd., a comprehensive machine tool manufacturer with a long history of about 120 years, has previously built such a flexible manufacturing factory "Dream Site2" to produce a variety of small and medium-sized lathes and grinding machines.

The factory has applied a large number of technologies such as the Internet of Things, big data, and artificial intelligence to realize flexible manufacturing of extremely complex machine tools and grinders, becoming a typical example of smart factory construction.

For CNC machine tools, it is particularly difficult to achieve large-scale personalized customization. It is necessary to know that machine tool manufacturing often requires processing, assembling and manufacturing thousands of parts.

In order to achieve this goal, Japan's Okuma and Hitachi have carried out collaborative innovation, which is to ingeniously combine Hitachi's software and hardware technology advantages with its own manufacturing experience.

The solution is that "Dream Site2" uses robots and FMS (flexible manufacturing system) to effectively improve production efficiency.

At the same time, in terms of speeding up the shop floor control cycle and promoting production visualization that promotes overall optimization, an IoT environment using technologies such as RFID (wireless IC tag) established by Hitachi Manufacturing Co., Ltd., Owon Business Office.

This technology can collect and use 3M information of operators (Man), equipment (Machine), and materials/parts (Material) in real time, successfully cutting the development cycle of representative products by half.

The fundamental reason for the substantial increase in production efficiency is that Hitachi has effectively integrated the technology and experience of OT (Operational Technology) and IT (Information Technology).

In addition, "Dream Site2" also uses Hitachi's IoT platform "Lumada"'s production plan optimization solution.

The result of this is that the flexible manufacturing "Dream Site2" can further shorten the development cycle while being more flexible to respond to emergency plan adjustments.

At the same time, another typical feature of smart factories is the predictability of equipment status. It should be known that in traditional factories, the frequency of equipment failures is more difficult to predict than people think. Usually, a single equipment failure may cause the entire production line. The economic loss caused by downtime is even immeasurable.

The smart factory turns the passive maintenance method in the past, that is, maintenance only when the equipment fails, into preventive maintenance in advance.

Mainly by constructing a set of data models that can effectively determine the operating conditions of equipment, predict different types of failures, prevent problems before they occur, and effectively reduce the losses caused by equipment failures, so as to realize the 24-hour non-stop of the factory.

The key behind this is that there are high requirements for factory data collection and the interconnection of factory equipment. It is necessary to use a variety of sensors to perform big data analysis and modeling on mobile data.

But this is also a skill especially lacking in traditional enterprises. Hitachi also helped Curadian Electronics Co., Ltd. in Wuxi, Jiangsu build such a smart factory.

Wuxi Curadian Electronics is the world's major MLCC (chip ceramic capacitor) manufacturer, and its output accounts for about 15% of the global market share.

When electric vehicles, mobile phones and other industries usher in a major explosion, this also requires Wuxi Cundian Electronics to upgrade its production capacity to meet the large-scale demand of the market.

However, compared to the advance prediction of the state of machinery and equipment, the capabilities of this smart factory are more than that.

For example, from the perspective of cost and spare parts management optimization, Wuxi Cundian Electronics' smart factory has also achieved a true understanding of the operating status of production equipment.

In the future, various factories will be opened up to achieve coordinated development. Through a network cable and a platform, the overall management of multiple factories will be realized, and it will become a true "factory of the future".

In fact, such cases are not rare in China. Taking the cooperation between Hitachi and China Resources Sanjiu Pharmaceutical Co., Ltd. (hereinafter referred to as China Resources Sanjiu) as an example, it profoundly explains the importance of collaborative innovation in the intelligent upgrading of manufacturing.

As early as 2015, the cream workshop of China Resources Sanjiu Guanlan production base began to cooperate with Hitachi to enhance the core competitiveness and industry advantages of the company by introducing MES.

In the process of collaborative innovation, from the beginning of data collection and business inspection, the Hitachi team went deep into the production site to understand various processes. In the process, the two parties overcame numerous difficulties, and it took up to two years.

In October 2017, the system introduction and acceptance was completed. The MES system of the cream workshop of China Resources Sanjiu Guanlan Base passed GMP certification and became a pharmaceutical production workshop using electronic batch production records throughout the process.

At that time, such a whole-shop electronic batch record pharmaceutical production workshop was one of the few in China. Through collaborative innovation, China Resources Sanjiu realized the intelligent manufacturing of pharmaceutical production and pioneered the industry trend.

In October 2018, the cream workshop of China Resources Sanjiu Guanlan Base also implemented other information systems such as ERP (Enterprise Resource Planning), WMS (Warehouse Management System), QMS (Quality Management System) and DMS (Document Management System) with Hitachi. Fully integrated.

In the follow-up, Hitachi also participated in the implementation of the integration with the data acquisition monitoring system (SCADA) and equipment control system, which improved the timeliness of equipment data recording.

In May 2020, China Resources Sanjiu Guanlan Base was therefore awarded the "2020 China Benchmark Smart Factory", which is the industry's authoritative recognition of the level of China Resources Sanjiu's intelligent manufacturing.

Collaborative innovation, intelligent manufacturing. During this series of processes, it can be seen that Hitachi is not only a solution provider, but also a co-creator throughout. Through the unremitting efforts of both parties, it has helped China Resources Sanjiu Guanlan Factory achieve a magnificent transformation.

Of course, this is only the first step. As time goes by, I believe that the road of collaborative innovation between Hitachi and China Resources Sanjiu will go further and further.

The recently launched 2020 Shanghai International Import Expo is an important platform for global foreign companies to show their open and innovative ideas.

Hitachi, who has participated in the conference for three consecutive sessions, once again brought its innovative technologies and equipment in the fields of smart manufacturing, healthcare, and smart cities, which brought many surprises and inspirations to the participants.

03  Hitachi social innovation to make the world full of vitality

Smart manufacturing is not a far-reaching imagination, the digital factory has already arrived. Who brought this change, and where will it go?

It can be expected that Hitachi will create successful cases of smart factories through collaborative innovation, which will give more companies more reference and inspiration in the future.

The experience of these leaders can be a beacon for other companies and provide more professional guidelines for breakthrough upgrades, thereby promoting the systematic optimization of production in the Chinese manufacturing industry.

In this process, social innovation is of utmost importance. People want to live in a more comfortable, safe and healthy society. With this vision, Hitachi strives to solve the various problems faced by society and realize the "beauty" that people yearn for. This is the "social innovation" created by Hitachi and many partners. 

And how to make the world full of vitality, Hitachi will gather global wisdom and creativity to realize an environmentally friendly society, enhance customers' corporate value and improve people's QoL (Quality of Life). This will not only solve the current problems, but also become the driving force to revitalize the future.

Thursday, November 5, 2020

Hang Seng Electronics: Based on the financial scene, maximize the value of AI

 "In the current financial field, artificial intelligence is a key technology that assists financial institutions in conducting business."


Finance Xiaobai wants to pick a good stock? AI can help. From the smart recommendation of stocks, to the risk control system for financial management, and even the customer service to answer your financial questions, AI is behind them.

Hang Seng Electronics Co., Ltd. ("Hang Seng Electronics" for short), as a financial software and network service provider focusing on the financial industry, is well versed in the combination of AI and financial scenarios.

"In the financial industry, AI is not the icing on the cake, but a necessity for the operation of the industry." Lin Jinshu, a senior technical expert in artificial intelligence of Hang Seng Electronics and head of the NLP (Natural Language Processing) team of Hang Seng Research Institute, joined Hang Seng Electronics five years ago Faced with the increasingly complex data requirements of the financial industry, he took the lead in forming the artificial intelligence team of Hang Seng Electronics and exporting its technology to the entire industry.

Instead of labor, AI is fully penetrating the financial industry

According to Lin Jinshu, AI has already penetrated all fields and links of the financial industry. Securities, futures, funds, trusts, insurance, banks, exchanges, private equity... Where there is data, AI can be effective.

Take a daily application scenario-stock account opening is now operated by mobile phones, and there is no need to go to the trading department to provide identification as a few years ago. Face recognition, voiceprint recognition and other technologies allow investors to "brush face" and "record" to complete identity verification.

"However, the current customer service labor costs are very high. If you encounter a bull market, a large number of customers may flood the platform for consultation in a short time. This will put a lot of pressure on the customer service department and reduce the customer service experience."

Lin Jinshu revealed that in the field of customer service, AI is replacing labor in a large proportion, thereby saving manpower, space, equipment rental and other costs. For example, Tianhong Fund is behind the AI ​​customer service of Hang Seng Electronics providing technical services. In the entire financial industry, AI also plays an important role in process reengineering and promoting the digital upgrade of the industry.

For example, risk control, how to reduce risks? Collecting data and establishing a database of black and white credit risk lists are common practices. In the era of massive information, AI can effectively expand the amount of information in a short time. Through the collection and retrieval of massive data such as online news information, announcements, research reports, etc., the credit evaluation of the target is carried out, the risk judgment is made in advance, and the target is achieved. Real-time monitoring. Once the target has negative public opinion, AI can push relevant information in real time. With the help of AI, the data processed in two hours can now be completed in five minutes.

In the investment banking business, AI can also effectively replace manpower. For example, when submitting an IPO application, under the traditional mode, most of the human review methods are adopted, which is prone to oversight. By reviewing investment bank drafts through NLP technology, this scenario can be transformed. AI can not only check for errors in manuscripts, but also monitor public opinion information related to the subject matter when performing business links.

"In other fields, AI may play an auxiliary role. But in the current financial field, artificial intelligence is a key technology to assist financial institutions in conducting business ."

IT capabilities, algorithms, and business are indispensable

At present, the AI ​​system of Hang Seng Electronics has been extended like a tentacle and firmly embedded in different scenarios in various financial fields.

Hang Seng Electronics, born in 1995, has focused on the development of the financial industry since its establishment. From 8 founding employees to a team of nearly 10,000 people, from self-built office buildings to the upcoming headquarters building of more than 200,000 square meters, Hundsun Electronics has made great strides along the road of corporate development.

For 13 consecutive years, Hang Seng Electronics has been selected as one of the IDC Fintech 100 Global Fintech 100 list. In 2003, the Hang Seng e Shanghai Stock Exchange main board listed code 600570.

In 2017, the tide of artificial intelligence has swept into the financial industry. The country has introduced many artificial intelligence-related policies, and securities and fund institutions have also voiced one after another. AI technology is needed to empower the industry. This allowed Hundsun Electronics to see an opportunity, and they began to accelerate research and development in the field of artificial intelligence.

Lin Jinshu said that it is not easy to lead a department from scratch. There is a shortage of talents, lack of experience... Everything has to be explored by yourself. The biggest difficulty is the lack of understanding of artificial intelligence.

"At first, I thought artificial intelligence was an algorithm problem. But in practice, I discovered that there are many excellent algorithm engineers in the world, but they have not done well with artificial intelligence because they don't understand the business."

"Like Alpha Dog playing chess, the algorithm is fixed like a chess board, but the specific strategy of how to play chess requires a person who can play chess, that is, a person who understands business to specify." Lin Jinshu used "play chess." To explain, "Artificial intelligence requires IT capabilities, algorithms, and business, all three elements are indispensable."

After clarifying the development ideas, Lin Jinshu began to build a framework. Technically, he decided to look at the world on the "shoulders of giants" and invited academic experts such as Zhejiang University and Fudan University to serve as consultants. In terms of business scenarios, Hang Seng Electronics has extensive experience in financial business scenarios. The combination of technology and business has put Hundsun's AI development on the fast lane.

Based on the financial scene, build AI barriers

Lin Jinshu repeatedly emphasized that the development of AI is inseparable from a deep understanding of business scenarios.

He believes that among the three elements of artificial intelligence, business is the most important. On this basis, the depth of business understanding is the key to building a protective wall and defeating competitors.

He still remembers that the first AI project that Hang Seng Electronics landed was a cooperation with a leading brokerage firm. At that time, the reason why Hang Seng Electronics took the lead in the competition with Microsoft and IBM was that it provided a set of solutions based on the financial scene.

He said that the financial field has its own uniqueness. There are many professional terms when trading, and investors often ask many professional questions. This requires intelligent customer service to integrate with the knowledge background to answer.

For example, the four words "transaction failed" have different semantics when entered on e-commerce platforms and investment platforms. "We have tried, and for the same problem, we borrowed the algorithm of the e-commerce platform on the investment platform, and the accuracy is only one percent." Semantic understanding and the special nature of the processing flow make AI in the financial sector a rigid demand.

At the same time, in the current era of information floods, information often appears asymmetry. How to accurately distinguish between individuals and companies? At this time, multi-dimensional data is needed instead of single data judgment, which portrays the credit portrait of individuals and enterprises.

Lin Jinshu believes that the current AI development of the financial industry is still in its infancy, and the future development of AI will focus on a certain vertical scenario. This is an industry that requires long-term planning and many investments. For this reason, Hang Seng Electronics has made preparations. In the next two to three years, the artificial intelligence team under his jurisdiction will usher in rapid expansion.

To maximize the value of AI in the financial sector, this is what Hang Seng Electronics wants to do.

Talk about artificial intelligence

(Q-Daily Business Daily A-Lin Jinshu)

Q: What do you think of the development of Hangzhou's artificial intelligence industry?

A: Talent is the foundation for the development of the AI ​​industry. First-tier cities such as Beijing and Shanghai are easier to attract technical talents in the financial field. However, due to the high cost of living and entrepreneurship in first-tier cities, we have found that more and more talents come to Hangzhou for development in recent years.

Q: What kind of AI talent do you think financial institutions need?

A: For the completion of an AI product or project, the most indispensable are compound talents, including "IT+AI" (algorithm engineer + AI platform R&D engineer), "business + AI" (AI architect) and There are three types of "business + IT" (data engineer).

Q: Under the epidemic, various industries are accelerating digital transformation. Do you think the financial industry has an impact?

A: Actually, the digital transformation of the financial industry is very fast, and it has long been separated from face-to-face transactions. The epidemic has little impact on this. However, the voice of digital transformation has given AI technology a better development space, which is still good for us.

Q: Please talk about the entrepreneurial environment in Hangzhou.

A: Hang Seng Electronics has received strong support from governments at all levels in the development process, especially the Binjiang District Government. We have solved various problems encountered in our development in a timely manner, and helped us solve the park environment, construction site construction, transportation, etc. problem.

Q: What problems do you think the development of AI in the financial field is currently facing?

A: Data accuracy, security and privacy issues are worthy of attention. It is hoped that the government, society, media, and enterprises can jointly accelerate the development of effective data and the sharing of data resources.

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