Answers to Modern Manufacturing System Test Questions in Shandong University Network Education

What is the definition of manufacturing system manufacturing? Manufacturing is the process of transforming raw materials and information into various items to meet human needs. From this definition, we can see that the manufacturing industry should not only transform raw materials, but also transform a large amount of information into commodities that everyone needs, especially since the rapid development of the Internet in the early 1990s, information has played an increasingly important role in the manufacturing industry. In today's world, whether it is production, sales or market, information is regarded as the module of infrastructure. Broadly speaking, many systems can be used as prototypes of manufacturing systems.

The development of modern manufacturing system is 1. Concurrent engineering is defined as follows: Concurrent engineering means that designers, technicians, quality control personnel, manufacturers, marketers, and sometimes even cooperative manufacturers and user representatives work together from the initial stage of product development, so that all departments can evaluate whether the design is reasonable from their own perspective. In order to make the basic concept of concurrent engineering clear, we can understand it through the following production process diagram: Figure 1-3 Production process diagram Because the source of manufacturing system is from user demand, from user demand to function to the physical domain of the whole product, for example, to produce a computer, some hardware and shapes need to be designed, so the manufacturing process of the product is basically divided into four fields: the first is user field, that is, from understanding user demand; The second is the functional field, that is, from the needs of users to what functions products need to provide; The third is the physical field, that is, how to realize the function of the product through some software and hardware; Finally, the process is how to assemble software and hardware through manufacturing to provide more perfect products. The four fields and levels of the manufacturing system are as follows: Table 1- 1 Material Software Business Organization of the manufacturing system. The characteristics of users' domain performance, expectation of return on investment and customer satisfaction: four domains and four hierarchical tables of manufacturing systems; natural planning; business objectives; functional domains; microstructure input variables; business structure planning; office process domains; steps; subprograms; resources; human resources; traditional production is a one-way process; from users to manufacturing, the whole process is an upgrading process. Nowadays, the market is changing very fast, and customers' needs often cannot be accurately understood and obtained through the market. In this case, it is necessary to cooperate closely from the user field and the process field. So now we advocate concurrent engineering. The so-called concurrent engineering refers to the investigation of user domain, the design of functional domain, the production and manufacturing of physics and technology, etc. , and it is carried out simultaneously by teaming up. By parallel, we mean to proceed at the same time. The advantage of concurrent engineering is that each link can be quickly adjusted to meet the market demand. The members of concurrent engineering team include planning manager, project manager, design engineer, manufacturing engineer, process engineer and product manager. 2. Design for manufacturing In addition to designing products, factories also need to design production processes. In the past, it often happened that the people who designed the products did not cooperate with the people who designed the process, which usually led to serious problems in manufacturing. The popular trend now is to combine product design with process design. When designing products, we should not only consider customers, but also consider the difficulty of manufacturing. If a very good product is very difficult in the manufacturing process, it will greatly increase the manufacturing cost, and the product may not meet the market demand after its launch. The combination of product design and process design makes product manufacturing easier and more economical. Therefore, the combination of product design and process design (DFM) should take product design as the first step of manufacturing process design, and product design must start from the perspective of "easy manufacturing" and "economical manufacturing". 3. Computer Aided Design From the early 1990s to today, the network has developed for nearly 15 years. During this 15 year, the sharp drop of communication cost has brought a fundamental revolution to the global manufacturing industry, and the information product revolution has affected all aspects and steps of human beings, including manufacturing industry. Now, the design and development of a product can be in one country, the manufacturing and production can be in another country, and the market can be in a third country, so that the achievements of each country and region will be clearly divided and defined. From design and manufacturing to listing, the product flow can be broken down into many units, and each unit can be completed in the cheapest place in the world. Products can not only meet the market demand, but also have low prices, and the whole manufacturing supply chain is very flexible. Because of the use of network, many manufacturing processes and even designs are completed by computer. CAD is the abbreviation of Computer Aided Design. There are many such softwares, including CAM computer-aided management and CAPP computer-aided process control software. All software can exchange data together, which makes the information flow in the world be enjoyed and used quickly. In this way, many large companies can spread all over the world, including Microsoft, IBM and other companies. They not only set up a manufacturing center in China, but also set up an R&D center, which makes the information flow increase rapidly. R&D can be carried out 24 hours a day, and so does the manufacturing industry. Nowadays, many factories use day and night shift duty, and computer-aided design makes the whole information flow smoother. Features of Computer Aided Design (CAD): Computer Aided Software is widely used not only in product design (CAD), but also in process design (CAPP) ◆ Global design, manufacturing and market ◆ Low communication cost. 4. Group technology Group technology uses the similarity of parts (shape, size, processing technology) to perform multiple tasks. At first, it was mainly used as a process organization method to organize production technology preparation and production process management reasonably. With the continuous improvement of parts classification and coding system and the combination of group technology and computer application, the application of group technology has been extended to product design, process design, production planning, facility layout and other links. Many countries have made contributions to the emergence and development of GT. 1959, Mitrovanov founded GT, and Opitz of Ahern University of Technology led the formulation of "workpiece classification and coding system". The United States and Japan combine group technology with numerical control technology and computer technology, which creates the necessary conditions for developing CAD, CAPP and establishing FMS based on group technology. The advantages of group technology are as follows: machine tools and process equipment with high degree of specialization can be used; production equipment and workers can be equipped according to certain production procedures and the processing workload of each process; equipment can be arranged according to the typical process sequence of parts family to make the logistics smooth; workpieces can be transferred in parallel or in parallel order between processes to shorten the production cycle and reduce the work in progress; and economic responsibility system can be implemented for production units. Give full play to everyone's enthusiasm. Creative Flexible Manufacturing System (FMS) Flexible Manufacturing System (FMS) is an automatic manufacturing system controlled by computer based on CNC machine tools (NC) and machining centers (MC), which is suitable for small and medium-sized batch production of various varieties. Its characteristics are: multiple different workpieces can be processed at the same time; after a machine tool processes a part, it can be adjusted without stopping. According to the instructions of the computer, the connection between machine tools is flexible, and the transmission of workpieces between machine tools has no fixed flow direction and rhythm. Flexible manufacturing system is developed from western developed society, and this concept was first put forward by two manufacturing powers, Japan and the United States. The so-called flexible manufacturing system refers to the great flexibility of the whole manufacturing system. To achieve great flexibility, the method adopted by western developed countries is to use a large number of robots and a large number of manufacturing centers. The same manufacturing center can produce different parts, and as a result, the whole assembly line can be quickly replaced according to production needs, which will make the product assembly line very flexible. Flexible manufacturing system has been developed for 20 years. The whole flexible manufacturing system used to be a very popular concept in western countries, but now it has become a dead end. At present, the manufacturing industry in China is developing rapidly, and the momentum of development is very strong. Apart from China's extremely cheap human resources, the biggest consideration is that China has the greatest flexibility. Figure 3- 1 Whether the random shooting in the shooting experiment can be done well depends mainly on two aspects. The first is whether you can hit the bull's-eye every time. The second is not only to hit the bull's-eye accurately once, but also to hit the bull's-eye accurately every time. For a long period of time, if repeated attacks are needed, there must be some randomness. The production line also has two directions. The first is to produce good products every time, and the second is to produce suitable products for a long time. Just like the shooting experiment, none of the bullets hit the bull's-eye, but all of them hit the outside of the target. The second picture, not only missed the bull's-eye, but also was beaten in a mess. All three pictures are in the upper right corner, very concentrated and accurate, but they are not in the bull's-eye. In this case, you can hit the bull's-eye by adjusting the bull's-eye and sight, or changing the trajectory; The targets in the four pictures all hit the bull's-eye, which is both concentrated and accurate. This is the goal that needs to be achieved in the production process, that is, strong construction. Robustness, also translated as robustness, robustness and robustness, is one of the terms in control theory. It is the key to the survival of the system under abnormal and dangerous conditions, such as whether the computer software can not crash or crash under the conditions of input error, disk failure, network overload or intentional attack, which is the robustness of the software. The so-called "robustness" means that the control system maintains certain performance characteristics under certain parameter perturbation (structure and size). According to different definitions of performance, it can be divided into stable robustness and performance robustness. The fixed controller designed for the robustness of closed-loop system is called robust controller. The research of control system robustness is a very active field in modern control theory research. The problem of robust control first appeared in the study of differential equations in the last century. Blake first applied robust control to one of his 1927 patents. In 1960s and 1970s, the formation of state space structure theory was a major breakthrough in modern control theory. The structural theory of state space includes controllability, observability, feedback stabilization and the state space realization theory of input-output model. Together with the optimal control theory and Kalman filter theory, it makes modern control theory form a rigorous and complete theoretical system, and has made amazing achievements in aerospace and robot control applications. With the development of robust control theory, many remarkable theories have been formed. Among them, control theory is the most successful and perfect theoretical system to solve the robustness problem at present. Zames first put forward this famous theory in 198 1. He considered the control system of single-input single-output system and designed a controller to minimize the response of the system to interference. In the 20 years since he put forward this theory, many scholars have developed this theory and made it more widely applicable. At present, the research focus of this theory is the control problem in nonlinear systems. In addition, there are some theories about robust control, such as structural outlier theory and interval theory. Variation: * * Homogeneity and special reasons In production, not only accuracy but also concentration are required. Every part of every production process is different, and as a result, the total finished product will have a distribution map. If the production process is relatively stable, the final distribution map should be normal, but in actual production, the real target will be different from the current situation, just like in the shooting experiment, it is likely that all the shots are in a concentrated place, but not in the bull's-eye, that is, the average value is different. At this time, the average value may be biased. Second, the lens is scattered and the tolerance is large, so the normal distribution map will be biased. The reason for the variation is that * * * is different due to special reasons, as shown in the following figure: Figure 3-2 Normal distribution, when many blocks are together, a pattern will be formed. If the process is stable, the obtained distribution map is as follows: Figure 3-3 The distribution map of multiple pieces of normal distribution after deviation may have the following situations or a combination of several situations: Figure 3-4 If the normal distribution after deviation has only the same reason, the product distribution map of the process is stable and predictable. As shown in the figure below, the first four images are size statistics images generated in the time axis. Because the product distribution of the process is stable, the fifth diagram can be deduced, which is indicated by the dotted line: the process predicted in Figure 3-5 is produced, but if there are special reasons, the distribution diagram of the process is unstable, that is, unpredictable. For example, as shown below, there are differences in process products every time. Therefore, there is no scientific basis for the prediction of the fifth process product, and this prediction has no credibility. Figure 3-6 Unpredictable Process There are often two possibilities for a production process, one is special reason or special reason, and the other is the same reason. Special reasons refer to the reasons that cannot be known and controlled in advance in the whole production process, such as today's weather, employees' early and late work, etc. These factors are all special reasons and have unpredictable possibilities, so the result will make the whole production line unpredictable. For example, in the following operation diagram, with the time axis as the horizontal axis and the product as the vertical axis, we can see that after about 20 times of production, the diameter of the product has changed and has been rising for several points until 30 points. In this process, there may be some changes in the production process, but just looking at this picture, we don't know what has happened to the assembly line, so there is no way to prevent it. Figure 3-7 Variant Operation Diagram Process Control Statistics The purpose of process control is to control the process according to the above situation. Only by solving the special reasons can the process be better controlled. Therefore, it is necessary to analyze the reasons and then fundamentally solve the reasons, and then take corrective measures to ensure that the same problem will not occur next time. Statistical process control can be used here to remove special reasons, so as to ensure that there are no special reasons next time, so as to ensure that corrective measures will make the whole process stable for a long time. The purpose of statistical process control can be simply summarized as: find out the interference (special reason) and take corrective measures. The purpose of statistical flow control can be shown in the following figure: Figure 3-8 The purpose of statistical flow control introduces statistical control methods, and the central limit theorem, the so-called central limit theorem, is the core: ◆ A large number of independent events have a continuous probability distribution graph, which is normal distribution ◆ Increasing the number of samples will increase the accuracy of average estimation. From the definition of the central limit theorem above, it can be seen that once the continuous probability distribution diagram of normal distribution is large enough, the final result must be the result of normal distribution, which can increase the number of product samples and improve the accuracy. So if you want to know the determination of 100%, you can use 100% sampling. The more samples are sampled, the higher the accuracy. The application of this method in the production process originated in Japan. After World War II, Japan hired many American experts, mainly Suha Deming, who introduced them to how to use statistical methods to control the production process. The following figure shows the control chart established by 100 samples, with an average of 10 samples each time. Figure 3-9 Shewhart control chart based on 100 samples, with an average of 10 samples each time. In the figure, the upper limit is UCL, the lower limit is LCL, and the population size is 5.