You must be familiar with the term Industry 4.0, but it is more difficult to explain exactly what Industry 4.0 is.
Do you remember the tailor's shop down the street? The service is warm, the clothes fit well, and the tailors offer free after-sales services, such as trimming your waistline when you put on weight.
Before the First Industrial Revolution, tailors, carpenters, and blacksmiths approached customers at fairs, learned what they wanted, and made things on the spot. After the second and third industrial revolutions standardized and globalized market activities, producers and consumers were separated by a yawning gap called "sales and distribution channels." Now, the retail revolution, initiated by the Internet, has unleashed a burst of personalized demands, igniting the Fourth Industrial Revolution. So, with the help of technologies such as the Internet of Things, blockchain, artificial intelligence and cloud computing, modern manufacturing companies are once again gathering in the bazaar to "tailor" each customer on an industrial scale, following in the footsteps of their predecessors. This is Industry 4.0.
Specifically, the essence of Industry 4.0 is to meet the individual needs of customers with the unit cost of industrial production, and to minimize the waste of material resources while realizing economic growth.
1. Let's take a look at the challenges facing manufacturing enterprises
First, the manufacturing company needs to know the size of each customer, and then the product design or engineering team designs the product. This alone poses two big challenges for manufacturers. First, how do you tailor millions of customers around the world? Second, how can the R&D team design a product to meet the needs of each customer? Even if manufacturing enterprises find solutions to these problems, modern industrial production is based on mass production of standardized products, neither workshop equipment nor office processes can respond quickly to highly personalized product needs.
In addition, because the global division of labor has greatly stretched supply chains, a finished product can go through more than 10 separate production processes, with companies from more than 10 different countries or regions working together to complete it. Even a small change in demand will have an impact on the supply chain, and highly personalized product demand will cause a bullwhip effect on the supply chain, which will lead to excess inventory of raw materials, semi-finished products and finished products.
So manufacturers face three challenges.
1. How does the R&D team interact with each customer like a community tailor shop?
2. How to organize workshop production and respond to customers' personalized orders in a timely and effective manner?
3. How to organize global supply chains to minimize the bullwhip effect?
In the face of these challenges, simply implementing one or two IT solutions will not solve the problem. We need a complete transformation of the existing manufacturing management model.
2. However, the transition will not be easy
In the field of "product life cycle management", although this theory has been put forward more than ten years ago, most manufacturing enterprises actually implement "product data management" for product design. Moreover, due to the lack of technical investment in the field of after-sales, the manufacturing enterprises cannot track the actual use of the products by customers. Therefore, we need to shift our focus from a focus on product design to a focus on using the product and improving the experience of each customer.
In the "order to delivery" world, the traditional waterfall model of production planning in the office and execution in the workshop is separated. "Sales forecasting" becomes the core of production, and all production work revolves around this assumption. This kind of waterfall production mode not only has a longer production cycle, but also has a higher risk. Once the forecast is wrong, or the demand of a single customer changes, or even the demand side or the production side of the accident, can not be able to respond in time. Therefore, we need to move from a waterfall manufacturing model to an agile manufacturing model where offices work closely with the manufacturing floor to understand the availability of production resources in real time and dynamically match customer orders to production resources.
In the field of "supply chain management", although "supply chain management" requires transparency of information to all participants, in practice, most manufacturing enterprises only use "supplier relationship management" in order to obtain the maximum profit from upstream and downstream partners. As a result, ecosystem collaboration is still a new concept for most manufacturing companies, and information between raw material suppliers, component manufacturers, warehouses, and transportation companies cannot be shared in real time. We need to find a mechanism that allows all participants in the supply chain system to share trusted information in real time, thus breaking down information barriers and enabling efficient collaboration.
If the paradigm shift just described is successful, manufacturing companies can move from a rigid organization centered on internal processes to a highly agile organization centered on customers. Can not only respond to external customer needs, but also respond to unexpected events with a high degree of agility.
Hearing this, you may have a question. Why do these pattern shifts make sense now, but they didn't a decade or two ago?
3. That's because four increasingly affordable sets of supporting technologies are making this transition possible
The first set of technologies is the low-cost Internet of Things, which helps us connect the physical world to the informationized online world in real time. Through the information physics system, the physical world and the information world can achieve effective integration and real-time interaction.
The product design or engineering design team can not only go deep into the after-sales field to fully understand the use of the product, but also achieve continuous research and development, continuously improve the product in an iterative way, and dynamically link the customer order with the machine through the dynamic order path.
In addition, the supply chain management team can track the real-time movement of drivers, vehicles, and cargo, as well as the location and capacity of the warehouse.
The second set of technologies is blockchain, which, combined with IoT technologies, enables all businesses across the industry value chain to efficiently share trusted information through weakly centralized super ledgers. In order to help the industry value chain enterprises through the ecosystem collaboration, constantly improve the current business relationship.
With sensors and actuators installed on products and devices, mirrored into the information space, and information shared across the value chain via blockchain technology, we are faced with an unimaginable amount of real-time data and decision points. After-sales service team and r&d team in the past, enterprises may only need to track the usage of dozens of products, the production planning team only needs to be matched with dozens of hundreds of orders production line, supply chain management team only need to track thousands of cargo truck, decision-making team cycle may be a few weeks or months. Now we have data from hundreds of thousands or even millions of entities, with tens of thousands of possible combinations between them, and companies making decisions in a matter of seconds.
This requires a third set of techniques to "save the day". They are big data, optimization engines, machine learning and artificial intelligence technologies, which enable industrial IoT platforms to instantly collect millions of massive amounts of data, learn from them and find optimal solutions.
The fourth set of technologies is cloud computing, which will make the technologies mentioned above more affordable and widely available.
We learned about the operational challenges facing manufacturing companies, the management changes needed, and the supporting technologies. The next thing to know is how the blueprint of Industry 4.0 should be drawn? Where to start? How to start our journey of Industry 4.0?
4. Some manufacturers have been lulled into thinking that they can achieve intelligent manufacturing by buying automated production lines, only to spend millions of dollars on state-of-the-art hardware only to discover that they are still not "intelligent manufacturing companies"
Some manufacturers have equated the Internet of Things with smart manufacturing, retrofitting production lines with various types of sensors so that factory managers can monitor the production process through displays, but found that using them didn't bring much value.
Some manufacturing companies that have invested in predictive maintenance solutions supported by machine learning will also be disappointed with the initial accuracy of the predictive model.
Some manufacturing enterprises equate cloud computing with intelligent manufacturing, and they believe that moving ERP and MES to the cloud can make a leap in intelligent manufacturing.
As mentioned above, most manufacturing companies spend a lot of time and money on strategic planning, but most of what they get is fancy technical terminology that has nothing to do with actual operations.
IBM has an integrated approach that combines strategic blueprint planning, organizational and cultural development, information systems building, and continuous pilot. This approach can help manufacturing companies take a structured, holistic, and long-term view of their Industry 4.0 journey to achieve direct business benefits by driving learning across the organization.
The Blueprint Outlines a process that integrates customer-facing production resources, organizational structure, corporate culture and information systems with enabling technologies such as the Internet of Things, artificial intelligence, blockchain and cloud computing.
For example, in order to promote organizational and cultural development, a digital office or elite team can be set up to bring together members of engineering, manufacturing, supply chain, after-sales service and sales and marketing departments to learn and implement Industry 4.0 initiatives. Achieves major breakthroughs in after-sales service, continuous engineering, integrated office and workshop operations, and value chain ecosystem collaboration.
It is worth noting that when building an industrial IoT platform, it is necessary to integrate office business processes with shop floor operations, and based on this, to make more informed decisions based on data for personalized customer service, product design and supply chain optimization.
Finally, the journey of Industry 4.0 requires manufacturing enterprises to keep learning by doing. Instead of spending years planning a perfect solution, agile organizations take a "garage approach," starting with continuous prototyping, launching a minimum viable product or process first, and iteratively improving it by continuously gathering feedback from internal and external customers.
To conclude, in today's IBM Super IN episode, "Understanding Business," IBM offers the following insights:
● The essence of industry 4.0 is to meet the individual needs of customers in the industrial production unit cost, in the realization of economic growth at the same time, to minimize the waste of material resources.
● In the face of challenges, manufacturing enterprises need to transform in the three areas of "product life cycle management", "order to delivery" and "supply chain management".
● The journey of Industry 4.0 transformation is not easy. It needs to combine the overall blueprint planning with the agile "garage approach" to help manufacturing enterprises adopt a structured, comprehensive and long-term perspective to view the journey of Industry 4.0.
Macro morning long technology co., LTD. Is located in the guangdong zhuhai grand bay area between the three major urban belt -- -- -- -- -- zhuhai golden bay port industrial zone, since its inception, the company focused on intelligent three-dimensional warehouse, intelligent AGV carrying, wisdom and factory automation stereoscopic warehouse, intelligent dense warehouse, four to shuttle car, stacker, three-dimensional library shelves, automatic packing machine, AGV handling car, cold chain cold storage, robot palletizer, palletizer, logistics conveying system, automatic loading and unloading car system, automatic sorting and picking system, logistics automation equipment, information integration, MES manufacturing execution system, WMS warehouse management system, intelligent storage system, intelligent factory, edible oil filling production line, Filling production line, intelligent warehouse, packaging equipment and other intelligent equipment research and development, design, manufacturing, installation and debugging, technical services and packaging line solutions integration services. Company is mainly for edible oil, beverage, water, feed, new energy, cosmetic, pharmaceutical and other industries provide automated secondary packaging equipment (out of the box machine, packing machine, sealing machine), palletizing equipment and system (stacker crane, tear open buttress machine), intelligent three-dimensional warehouse (stacker, RGV/AGV dolly, three-dimensional shelf), transmission system, intelligent truck and other high-end intelligent complete sets of equipment Integration with the whole line system.
