We are now in a new era, there have been more than ever concepts: lean manufacturing, intelligent manufacturing, industrial 4.0, digital factory, industrial networking, big data industry, artificial intelligence …… however, to clarify how the concept so much between Relationship? Intelligent Manufacturing must serve the business, whether intelligent manufacturing for us, with which to explore the definition and implementation methods, we must be based on the business strategy as the goal. Corporate management is: ① ② provide quality products to consumers / customers to ensure return on shareholder investment ③ for the welfare of employees this business must be considered, but also the value of the enterprise as a whole lies. For the moment most of the discussion focused on intelligent manufacturing technologies to achieve, flaunt intelligent manufacturing production line, and more is a partial look at the overall situation, but on the other hand, in order to intelligent manufacturing and the system is also a departure from the nature of the business, how to clarify management and intelligent the relationship between manufacturing and the establishment of effective path analysis and judgment, and successive effective implementation of the overall strategy for enterprises, particularly important, because it is about long-term survival of the enterprise, rather than the short-term dividend policy. How each concept of the role? Although we can not call concept has been achieved, but there will be corresponding to the area where they explained. 1 is a digital Lean Lean is a foundation of continuous improvement of operating efficiency, resource plays, including the core strength of the people’s initiative, continuous learning and constantly improving, so that enterprises continue to enhance the competitiveness of eliminating waste is a kind of maximize the use of resources, cost-effective way to play, and ultimately to maximize the profitability of the business. Lean on the production of overproduction, waiting, transportation, over-processing, inventory, defects rework, walking, waste of talent has been focused, and made a lot of methods to eliminate. These closely related to the business objectives of manufacturing units. We always put the computer, MES / ERP them understand the digital system, however, the foundation of digitization is “digital” – is based on “quantitative management” scientific thinking management, therefore, the so-called essence of digital operations in the operation, rather than digital, digital means of digital operations just to achieve. The reason why the foundation is digitized Lean Lean that provides for the production of various quantization methods, tools, e.g. KPI, OEE, TPM, RCA, 5S, visual management, billboards, etc., so that these become a factory can be quantified, visualization, transparentFactory, everything serves the business objective: quality, cost and delivery capabilities. Smart Plant performance requirements are based on quantifiable lean and defined, these are digital operations, all the concept of intelligent manufacturing, industrial, etc. must be 4.0 to achieve the goal.
Smart plant performance requirements
2 automation traditional role, we will only stand angle automation industry automation appreciated, the sensor detects that the control loop, a display, alarm trends, however, when we put Automation intelligent manufacturing environment, we will find that it’s role is to serve the operational nature. Why (1) To ensure the efficiency of automation? From the point of view of traditional manufacturing operations, the use of manual handling, processing process obviously can not be compared with the speed of the machine, especially it comes to the production of integrated intelligent manufacturing will continue to reduce unnecessary intermediate links – do not lean value, as defined in link. In fact, the degree of automation, automated continuous production is higher. (2) to ensure the production of quality high-precision servo positioning and synchronization, robot integrated manufacturing makes the product quality and consistency continue to improve, these machines are compared to people in terms of a more important role. (3) provide production flexibility of motion control not only provides high-precision processing quality, but also ensures flexible production, just as in a variety of machines, motion control play a role to make production more flexible, parameter setting, the servo curve planning processing system itself Copyright control Engineering , to ensure a smooth handover process. (4) providing the uplink data acquisition and downlink instruction execution course, automation systems plays lean visual management roles, including trend, alarm, of course, include energy production, maintenance, quality and data delivery to the management system, of course, also receive instructions from the management system, such as a new order processing parameters, steps and the like. 3 digital / role information technology has made automation of standardized mass production to achieve a high level CONTROL ENGINEERING China Copyright , however, when the individual needs of production becomes more and more time on created new challenges, from the angle of lean, quality, cost and delivery have become difficult, a few examples to illustrate: defect rate: when the print gets smaller batches, boot waste will increase the defect rate, so that the actual qualityOn the decline; cost: when the defect rate increase, the cost is clearly improving, and personalized production brought about by the process switching time will cause costs to rise, when the machine will result in loss costs, from personalized products at cost point of view, must the cost allocation on each batch of product, then the production plan of energy consumption, machine efficiency becomes more important – significantly increases the cost. Delivery capacity decreased significantly: the time consuming process of switching, crashes, rework this in high-volume production has been very mature solution will be magnified in the era of personalization, making the delivery of decline. From this point of view to observe the manufacturing requirements will be found in the larger global to optimize the production line has become a necessity, such as: 1. How to make the largest collaborative production and operation processes to eliminate the middle of the time, energy consumption and other waste? 2. When the device has shut down the production line how to automatically distribute the load? 3. How to reduce waste in turn reduce the quality of batches of iterations decreases? 4. time-consuming process of switching how to reduce in order to achieve quick delivery? Go back to an operational perspective to think about, you will find transparent information to analyze the problem of intelligent manufacturing must rely on the data link up to observe the panorama of the production line, in order to seek to optimize operations. The manufacturing level of data collection due to the differences in vertical industry has always been a challenge, and in fact in recent years the project Intelligent Manufacturing operations in this issue more prominent CONTROL ENGINEERING China Copyright , resulting in a a lot of obstacles, and this is the reason why the OPCUA become hot because OPCUA to solve the following problems: ① shared data model so that the data objects easier, more convenient way possible for data collection; ② enables semantic interoperability can be made between the cross-platform data systems to interact based on standards and specifications; ③ vertical integration is more vertical industry information model provides a convenient data.
FIG. 1 is based on manufacturing information OPCUA / MQTT integration
OPC UA specification provides communication with the device layer, the data dictionary is provided in the management information model specification stage, included in the reference model of RAMI4.0 management shell (AdministrationShell), a standard data dictionary information are solved with the global business model level. This is an informational set of the horizontal angleto make.
Figure 2 standard architecture on intelligent manufacturing reference
not only to sort out the transmission of data, but also to understand the flow of data – that use, but also to serve the production operations. 2 from NIST on intelligent manufacturing-related standards, including from the bottom of the fieldbus, information model, data model, design, manufacture various links to form the panoramic gives us a reference. 4 Intelligent – global optimization and decision support automation based on the regulation of individual control tasks, even if the multi-variable system usually in a machine, a subsystem (such as refining, pharmaceutical process), whereas the production of global optimization to in higher dimensions, but this time, computing power, the ability to model beyond the current mechanistic models.
FIG. 3 from the lean operation to the intelligent several levels
FIG. 3 depicts an overall process favorites from lean to intelligent data acquisition, information processing, until the final use of the global self-learning ability. Therefore, summary, intelligence must establish a global optimization problems on lean operations, automation, information technology, through more global model, demand-side market pull, process design and aided manufacturing, supply chain (except traditional supply chain also includes smart grid, logistics), manufacturing sectors, operation and maintenance of the entire cooperative, they formed a whole based on device status, production orders, energy consumption, financial costs together constitute the “optimization”, and gives operators the “decision support.” Knowledgeable personnel training – not a digression knowledgeable Discussion of Personal Training is intelligent manufacturing base from lean to the intelligence process, consider the relationship between knowledge and personnel training is also essential for intelligent manufacturing. 1 knowledge – wisdom reuse resources who are the most important link in the entire manufacturing process, from Lean continuous improvement, to the automatic control of machine design, information technology and the intelligent learning Copyright Control Engineering All , which will depend on the wisdom of human transmission has become the “standard”, “standard”, reusable , so that knowledge can be a system that can be reused, and to upgrade their own learning, for final optimization decisions. Not only software reuse, people’s knowledge and experience must also be multiplexed, material and non-physical resources are the kind of time, and the wisdom, the experience is even more resources, from a cost point of view, The human experience has a great potential, which is much more important resource. 2 personnel training and education is the foundation of intelligent manufacturing
Figure 4 intelligent manufacturing talent knowledge structure analysis and planning
personnel training is the key to intelligent manufacturing, a variety of intelligent manufacturing for the global lack of knowledge comes from education the lack of training and a global system of thinking, from the specific point of view, intelligent manufacturing technology contains more global learning, including the professional development of automation to IT, the extension machinery, robotics, communications, PLCopen software ideas.