Enterprise resource planning (ERP) is a highly integrated computer management system, which comprehensively manages resources (people, finance, materials, information, etc.). ) owned by the enterprise. The corresponding computer management system has also gone through the basic MRP stage, closed-loop MRP stage, MRP-II stage and ERP stage.
5.3. 1. 1 Material Requirements Planning (Basic MRP)
With the help of the computing power of the computer and the management ability of the system to customer orders, inventory materials and product composition, the material demand plan can be formulated and calculated according to customer orders and product structure list. Realize the reduction of inventory, so as to achieve the purpose of "reducing inventory without shortage of materials"
MRP is mainly used in manufacturing. It has the management function of purchasing raw materials from suppliers, processing or assembling products and selling them to demanders. The operation and production activities of any manufacturing industry are carried out around its products, and the information system of manufacturing industry also embodies this feature. MRP is the integration of material information from product structure or bill of materials.
Material demand information, product structure, procurement and supply lead time and inventory information are the four main data for running MRP. The accuracy of these data determines the effectiveness of MRP.
MRP generally includes the following modules: Master Production Schedule (MPS) module, which is a plan to convert the product series or categories specified in the production plan outline into specific products or specific parts, and can make material demand plan, production schedule plan and capacity demand plan accordingly; Material Requirements Planning (MRP) module is used to calculate the time and quantity of material requirements, especially the quantity and time of related materials; The BOM module is used to calculate the product structure of each product and all the materials to be used; Inventory control (IC) module is a module that calculates the change data of all products, parts, products in process and raw materials of an enterprise according to the method of storage theory. The purchase order (PO) module is a module for ordering from suppliers; The production order module is used to generate orders for processed products.
5.3. 1.2 closed-loop MRP
Because the basic MRP is based on the following two assumptions: first, the production plan is feasible, that is, it is assumed that there are enough equipment, manpower and funds to ensure the realization of the production plan; The second is to assume that the procurement plan is feasible, that is, there is enough supply capacity and transportation capacity to ensure the completion of material supply. However, in actual production, the production capacity and material resources are always limited, so it often happens that the production plan cannot be completed. MRP system developed into a closed-loop MRP system in 1970s. Closed-loop MRP system not only integrates material demand planning, capacity demand planning, workshop operation planning and purchasing operation planning into MRP to form a closed system.
Simply put, the formation of closed-loop MRP is to add capacity requirement plan on the basis of basic MRP, and form a closed-loop system of "plan-implementation-feedback-plan". The normal operation of MRP system needs a realistic and feasible master production plan. In addition to reflecting market demand and contract orders, it must also meet the capacity constraints of enterprises. Therefore, in addition to making the resource demand plan, we should also make the capacity demand plan to balance the capacity of each work center. Only by taking measures to ensure that the capacity and resources meet the load demand can the plan be implemented. To ensure the realization of the plan, it is necessary to control the plan. When MRP is executed, the priority of processing is controlled by the dispatch list, and the priority of purchasing is controlled by the purchase order. In this way, the basic MRP system is further developed, and the functions of capacity requirement planning, execution and control planning are also included, forming a loop called closed-loop MRP.
5.3. 1.3 Manufacturing Resource Planning (MRP)
The appearance of closed-loop MRP system unifies all subsystems in production activities. But this is not enough, because in the management of enterprises, production management is only one aspect, only involving logistics, and logistics is closely related to capital flow. In many enterprises, accounting is managed separately, which leads to repeated data entry and storage, and even inconsistent data. Therefore, in 1980s, people integrated subsystems such as production, finance, sales, engineering technology and procurement into an integrated system, which was called Manufacturing Resource Planning System, abbreviated as MRP in English, and named MRP II to distinguish logistics demand planning (also abbreviated as MRP).
The main difference between MRP ⅱ and MRP is that it uses management accounting to realize the integration of material information and capital information, and manages the economic benefits brought by the implementation of enterprise's "material plan" in monetary form.
In MRP ⅱ system, based on the product structure of MRP, starting from the lowest material cost of purchased parts, the material cost, labor cost and manufacturing cost (indirect cost) of each material are accumulated layer by layer, as well as the cost of each layer of parts, until the final product is obtained. Then combined with marketing, the profitability of various products is analyzed.
The basic idea of MRPⅱⅱ is to take the enterprise as an organic whole, and from the perspective of overall optimization, use scientific methods to effectively plan, organize and control all kinds of manufacturing resources, production, supply, marketing and finance of the enterprise, so that they can develop harmoniously and give full play to their functions. MRPⅱⅱ combines traditional accounting treatment with accounting affairs, which not only manages the present situation of accounting funds, but also traces the ins and outs of funds. It generally includes the following modules: product data management module, master production planning module, material demand planning module, inventory management module, capacity demand module, sales management module, procurement module, workshop operation management module, financial management module and quality management module. These modules are independent in structure, but interdependent in function.
5.3. 1.4 enterprise resource planning
The concept of ERP was put forward by Gartner Group in the United States in 1990. Its exact definition is MRPⅱII II (Enterprise Manufacturing Resource Planning), the next generation manufacturing system and resource planning software. MRP ⅱ mainly focuses on the management of human, financial and material resources within enterprises. ERP system extends the management scope on the basis of MRP ⅱ. It integrates customer demand with manufacturing activities within the enterprise and manufacturing resources of suppliers to form a complete supply chain of the enterprise, and provides a complete supply chain for all aspects of the supply chain such as order, procurement, inventory, planning, manufacturing, quality control, transportation, distribution, service and maintenance, financial management and personnel management. With the rapid development of IT technology and the application of network communication technology, ERP system adopts client/server (C/S) architecture and distributed data processing technology, and supports Internet/Intranet/Extranet, e-commerce and electronic data interchange (EDI). In addition, it can also achieve interoperability on different platforms.
ERP integrates customer demand, manufacturing activities within the enterprise and manufacturing resources of suppliers, and forms a complete supply chain of the enterprise. Its core management ideas are mainly embodied in the following three aspects: ① It embodies the idea of managing the whole supply chain resources; ② Reflect the ideas of lean production, agile manufacturing and synchronous engineering; ③ Reflect the idea of pre-planning and control.
Shortly after the emergence of ERP, computer technology encountered the upsurge of Internet/Intranet and network computing, the internationalization trend of manufacturing industry and the deepening of manufacturing informatization. Intranet will be the choice of network construction for many large companies in the future. Using Web client has the advantages of low cost, convenient installation and maintenance, cross-platform operation and unified and friendly user interface. In addition, all database vendors support Web technology, so almost all client/server application developers plan to install the front end of Web browser on their products. Several large manufacturing software companies, such as Oracle Bone Inscriptions, sarp and BAAN, are scrambling to "network" their customers of MRP II/ERP clients/server applications.
5.3.2 Decision Support System
Decision Support System (DSS) is a computer-based human-computer interaction system that applies decision science and related theories and methods. Mainly facing the semi-structured and unstructured decision-making problems in the strategic planning of organizational management, it provides users with the convenience of obtaining data and building models, and assists decision makers in analyzing and making correct decisions. The concept of decision support system was put forward in 1970s and developed in 1980s. Its appearance is based on the following reasons: the traditional MIS has not brought great benefits to enterprises, and people should play an active role in management; People's understanding of the law of information processing is improved, and in the face of changing environmental needs, higher-level systems are needed to directly support decision-making; The development of computer application technology provides a material basis for decision support system.
5.3.2. Features of1DSS
According to the definition, the characteristics of decision support system can be summarized as follows:
(1)DSS is interactive. The research shows that decision-making can be completed through many conversations between managers and the system, and human factors such as preference, subjective judgment, ability, experience and values have an important influence on the decision-making results of the system.
(2) The problem solved by 2)DSS system is a semi-structured decision-making problem. The use of models and methods is certain, but decision makers have different understandings of the problem. The use of the system has a specific environment, and the conditions of the problem are uncertain and unique, which makes the decision-making result uncertain.
(3) The system has a special structure to store and learn standby models and methods, and provides the functions of model comparison, connection and synthesis. The driving force of the system comes from the model and the user, the user is the initiator of the system operation, and the model is the core of the system to complete the transformation of each link.
(4)DSS only plays an auxiliary role in decision-making. DSS should not replace the judgment of managers, but should let managers take the initiative and improve the ability of decision makers to make scientific decisions.
(5) The decision support system should be easy to learn, use and modify, so it is necessary to dynamically analyze the user's needs and improve the functions of the decision support system in time.
Model base, method base and database of 5.3.2.2 decision support system
(1) model base.
Information processing model is common in the field of management, and its manifestations are mathematical expressions, computer programs and so on. Through the establishment and use of the model, decision makers can obtain useful decision-making information. Modeling is a creative work for experts and scholars in the decision-making field to abstract their mathematical models while exploring the changing laws of things. It takes a lot of energy to get a regular or similar mathematical model.
After the mathematical model is established, an important problem is the solution algorithm of the model, which can be an exact solution or an approximate solution. This algorithm was put forward by computer numerical calculation scholars. With the model algorithm, you can program in computer language. The actual decision-maker can use the model program to execute on the computer, calculate the results and get the auxiliary decision-making information. Model is an important means to assist decision-making, and model base is a collection of models. According to a certain organization method, the models are collected and managed organically by the model base management system. The model base and the model base management system constitute the model base system.
(2) Method library.
Method base system consists of method base and method base management system. Its basic function is to provide users with the necessary algorithms to solve and analyze various models and methods for their decision-making activities. The methods in the method base can usually include various optimization methods, prediction methods, statistical methods, countermeasure methods, risk methods, matrix equation solving and so on.
The method library management system is responsible for the description, entry, storage, addition, modification and deletion of methods. The usual method is to choose an appropriate computer programming language, and turn the related algorithms into an executable program and store it in the computer. These programs can be described as functions or processes, and then the corresponding program models can be called according to the needs of solving problems, so as to achieve the purpose of solving problems. In addition, the method base management system should also have the ability to interact with database and model base, and provide flexible and convenient interactive public function for users to choose algorithms.
(3) database.
Database is a software system that collects, processes, stores and outputs information. Therefore, the development and application of model base and method base should be based on database. Only when there is a perfect database system and the fundamental guarantee of information can the model base and method base play a role. On the other hand, the development of model base and method base puts forward a new topic for the research and application of database, which promotes its research on how to provide a data model more suitable for the operation of models and methods.
Model base and method base are inseparable, and whether it is parameter estimation, model solution or model verification, it is realized by various methods. The richness and performance of methods in the method library determine the use effect of the model. In a word, from the point of view of assistant decision-making, "three databases" are the important support to solve the problem, and a powerful assistant decision-making system should have "three databases" and take them as the core.
Expert system
In the past 30 years, artificial intelligence (AI) has developed rapidly, and has been widely used in many disciplines, and achieved fruitful results. Expert system (ES), as an important branch of artificial intelligence, is a new applied science that came into being and developed in the early 1960s. With the continuous development of computer technology, it is becoming more and more perfect and mature. 1982 professor feigenbaum of Stanford university in the United States gave the definition of expert system: "expert system is an intelligent computer program, which uses knowledge and reasoning process to solve complex problems that require the expertise of outstanding people."
Expert system is an intelligent computer program system, which contains a lot of expert knowledge and experience in a certain field, and can use human experts' knowledge and problem-solving methods to solve problems in this field. In other words, the expert system is a program system with a lot of professional knowledge and experience. It uses artificial intelligence technology and computer technology to reason and judge according to the knowledge and experience provided by one or more experts in a certain field, and simulates the decision-making process of human experts to solve those complex problems that need to be dealt with by human experts. In short, expert system is a computer program system that simulates human experts to solve domain problems.
5.3.3. 1 General characteristics of expert system
Generally speaking, expert system has some characteristics and advantages.
(1) inspiration. Expert system can make use of experts' knowledge and experience to make reasoning, judgment and decision. Most of the work and knowledge in the world are non-mathematical, and only a small part of human activities are centered on mathematical formulas (about 8%). Even in chemistry and physics, most of them rely on reasoning; The same is true of biology, most medicine and all laws. The thinking of enterprise management depends almost entirely on symbolic reasoning, not numerical calculation.
(2) transparency. Expert system can explain its own reasoning process, answer the questions raised by users, make users understand the reasoning process and improve their trust in expert system. For example, if a medical diagnosis expert system diagnoses that a patient has a viral cold and must take some treatment plan, then the expert system will explain to the patient why he has a viral cold and why he has to take such a treatment plan.
(3) flexibility. Expert system can constantly increase knowledge, modify the original knowledge and update it. Because of this feature, expert system has a very wide range of applications.
The Structure and Types of 5.3.3.2 Expert System
The structure of (1) expert system.
Expert system usually consists of six parts: human-computer interaction interface, knowledge base, inference engine, interpreter, comprehensive database and knowledge acquisition.
1) knowledge base. The knowledge base is used to store the knowledge provided by experts. The problem solving process of expert system simulates the thinking mode of experts through the knowledge in knowledge base. Therefore, knowledge base is the key to the quality of expert system, that is, the quality and quantity of knowledge in knowledge base determine the quality level of expert system.
2) Global database. Comprehensive database, also known as global database or general database, is used to store the initial data of a field or problem and the intermediate data (information) obtained in the reasoning process, that is, some current facts of the processed object.
3) inference engine. According to the conditions or known information of the current problem, the inference engine repeatedly matches the rules in the knowledge base and draws new conclusions, thus obtaining the solution result of the problem. Here, there are two kinds of reasoning methods: forward reasoning and backward reasoning. Forward reasoning is to match antecedents with conclusions, and backward reasoning is to assume that a conclusion is established first to see if its conditions are met. It can be seen that the inference engine is just like the thinking mode of experts to solve problems, and the knowledge base realizes its value through the inference engine.
4) Interpreter. Interpreter can explain the behavior of expert system to users, including the correctness of reasoning conclusions and the reasons why the system outputs other candidate solutions. The interpreter can also explain the conclusion and solving process according to the user's questions, thus making the expert system more humanized.
5) Man-machine interface. Interface, also known as interface, enables the system to have a dialogue with users, and enables users to input necessary data, ask questions and understand the reasoning process and results. Through the interface, the system requires users to answer questions, answer questions raised by users and make necessary explanations.
6) Knowledge acquisition. Knowledge acquisition is the key to the superiority of expert system knowledge base, and it is also the "bottleneck" problem of expert system design. Through knowledge acquisition, the content in the knowledge base can be expanded and modified, and the automatic learning function can be realized.
Working process of expert system: knowledge is pre-stored in knowledge base (some expert systems can also acquire knowledge through learning), and users input information through human-computer interaction interface. On the basis of the knowledge and acquired information in the original knowledge base, expert system uses the coordination of inference engine and comprehensive database to complete the reasoning process and draw conclusions, and finally presents the conclusions to users in the form of multimedia.
(2) Types of expert systems.
1) Explain the expert system. The task of interpretation expert system is to determine the meaning of known information and data through analysis and interpretation. Such as satellite images (cloud images, etc.). ) analysis, integrated circuit analysis, dendritic chemical structure analysis, ELAS oil logging data analysis, chromosome classification, prospector geological exploration data interpretation and hilly water exploration and other practical systems.
2) Forecast expert system. The task of forecasting expert system is to infer what may happen in the future by analyzing what is known in the past and now. For example, expert system such as severe weather forecast (including rainstorm, hurricane, hail, etc. ), battlefield prospect prediction, crop pest prediction, etc.
3) Diagnostic expert system. The task of the diagnosis expert system is to infer the cause of an object's dysfunction (that is, failure) according to the observed situation (data). There are many examples of diagnosis expert system, such as medical diagnosis, electromechanical and software fault diagnosis, material failure diagnosis and so on.
4) Design expert system. The task of design expert system is to find the target configuration that meets the constraints of design problems according to the design requirements. Design expert system involves circuit (such as digital circuit and integrated circuit) design, civil engineering design, computer structure design, mechanical product design and production process design.
5) Planning expert system. The task of planning expert system is to find an action sequence or step that can achieve a given goal. Planning expert system can be used for robot planning, transportation scheduling, engineering project demonstration, communication and military command, crop fertilization scheme planning and so on.
6) Monitoring expert system. The task of monitoring expert system is to constantly observe the behavior of system, object or process, and compare the observed behavior with its proper behavior, so as to find abnormal situation and give an alarm. The monitoring expert system can be used for safety monitoring, air defense monitoring and early warning of nuclear power plants, national financial monitoring, epidemic monitoring of infectious diseases, crop diseases and insect pests monitoring and early warning, etc.
7) Control expert system. The task of control expert system is to adaptively manage the whole behavior of the controlled object or object to meet the expected requirements. Air traffic control, business management, autonomous robot control, operation management, production process control and production quality control are all potential applications of control expert system.
8) Debugging expert system. The task of debugging expert system is to give suggestions and methods to failed objects. The debugging expert system has the functions of planning, design, prediction and diagnosis. Debugging expert system can be used for the debugging of new products or systems, and also for the adjustment, measurement and testing of maintenance equipment in maintenance stations. There are still few examples in this regard.
In addition, there are decision-making expert systems and consulting expert systems.