LIFE CYCLE MANAGEMENT OF A NEW PRODUCT

ABSTRACT

In this article: we will get acquainted with the advantages of spiral model and IDEF0 diagrams, as well as life cycle management, PLM technology, PDM technology, the next stages of the life cycle similar to IDEF0 diagrams, product life cycle spiral model.

АННОТАЦИЯ

 В данной статье рассматриваются преимущество спиральной модели и диаграмм IDEF0, а также управление жизненным циклом, технология PLM, технология PDM, этапы жизненного цикла, аналогичные диаграммы IDEF0со спиральной моделью жизненного цикла продукта.

Keywords:  PDM data management systems, PLM technologies, product life cycle, CALS technologies, PDM technologies, life cycle, spiral model, IDEF0 methodology, IDEF0 diagrams.

Ключевые слова: системы управления данными PDM, технологии PLM, жизненный цикл продукта, технологии CALS, технологии PDM, жизненный цикл, спиральная модель, методология IDEF0, диаграммы IDEF0.

Introduction. One of the first publications on the application of system methods for programming the life cycles (LC) of objects of new technology is probably [1].  Already in prof. K. D. Zhuk generalized the theory of life cycle and logical-dynamic systems from the point of view of modern CAD systems, taking into account the level of development of information technologies of that period. [2] The flow of publications in mass media on lifecycle management (PLM) began at the turn of the century and is constantly growing. The role of PLM technology is the coordination of CAD/ CAM/ CAE and PDM technologies, which in the modern sense did not exist in the 1980-s. IGES-,CALS-technologies, STEP standard appeared, then more modern PDM-technologies, respectively, the concept of life cycle from a simple "philosophical" concept in design was transformed into a PLM-system - the coordinator of these technologies and standards [3].

PLM - organizational and technical systems that support life cycle management technology. They provide management of all information about change and related processes throughout the life cycle.

The IDEF0 methodology is used to construct a functional model of the life cycle. The model of creating a product of the "Black box" type can be decomposed into stages: 1) design; 2) production; 3) operation; 4) disposal. In fig. 1.The decomposition of the stage of designing the life cycle is presented. On the IDEFO diagram, the first functional block is "marketing", at the output of the block - "technical task (TOR)" - "product improvement".

Note that the CAE and CAD ∋ M1 software is used to implement the technical specification, and M1 is used to improve the production of CAD and CAM. Similarly, IDEF0 diagrams of the next stages of the life cycle can be given.

Figure 1. Decomposition of the "design" stage

PDM data management systems

PDM-technology (Product Data Management-technology) for managing product data and information processes of the life cycle [3]. Functions of PDM systems: management of storage of data and documents; process management; product composition management; classification. The main advantages of using PDM technology are: reduction of product development time; work automation; a significant increase in the share of borrowed or slightly modified product components (up to 80%) due to search. If necessary, PDM uses other data processing systems (for example, CAD-CAD).

Further development of PDM technology is PLM (Product Lifecycle Management) systems for lifecycle management. From a technical point of view, the PLM system ensures the integration of all information about a product in a single structure throughout its life cycle up to disposal of the product.

However, PLM systems are not limited only to the technological unification of data from automation systems of different stages of the life cycle system: the approach and solutions of PLM systems are aimed at streamlining the business processes of discrete production, uniting all disparate divisions of the enterprise, as well as its suppliers and customers.

The main benefits of using PLM: increased productivity, profits; overall reduction in material costs, achieved through detailed accounting of product requirements at the early stages of the life cycle and tracking their feasibility in the future, this makes it possible to identify most of the erroneous decisions in the virtual prototype of the product, and not in its physical embodiment. At the same time, the number of borrowed and standard solutions increases significantly.

System analysis of project activities.

Product design is provided by CAE (design), CAD (design) and PDM (document management) systems.

A computer-aided design system is described by the formula: .

The design object, considered as a "black box", has the form:

After receiving the technical specification for the design of the TO, the information retrieval system searches in the database for an analogue of the TO that most satisfies the task at hand. Intelligent design systems (ISP) belong to the class of standard variant design systems. ISPs are based on the knowledge contained in the metasystem.

Multiobjective optimization in the life cycle

Based on these parameters, the properties of the designed object ω_i, associated with functional restrictions, are calculated C_l^* <  f_l(α) < C_l^**  where f_l (α_i) are some functions of parameters that are specified in the knowledge base, or other requirements. When designing a product, TK should include its specified parameters α_i, the design process determines other parameters or selects the data of the symbolic model necessary for calculations.

With multi-criteria optimization, an integrated system of design and technological design is built. It is not easy to formulate a mathematical optimization problem in the presence of several quality criteria, the criteria are often contradictory, this was noted earlier, for example, by N.N Moiseevim, in [4].

Let us assume that the given criteria    need to reduce   (Sometimes they are limited to one of the most significant criteria; this approach often does not justify itself.)

Each of their scalar criteria   is called a particular criterion of optimality, and their totality   vector criterion of optimality.

We write the problem of multicriteria optimization in the form of a search for the set Pareto Р: where ) - criterion vector on the set of criteria. Promising application of the IPP method (research of the parameter space) This method is based on the construction and analysis of an admissible set of solutions using test tables and is implemented by the MOVI software package in an interactive mode.

Models of the presentation of the life cycle of a complex technical system

Academician N.R. Yusupbekov noted that there are several types of presentation of life cycle.

1. Linear (traditional sequential) model.
2. Incremental model, provides several increments (versions) with planned improvements. The customer can see the results earlier, change the development requirements, refuse or offer a better product.
3. The spiral model of life cycle, oriented to the technological object (TO), consists of 34 stages (rice. 2).

Using PLM technologies, you can limit yourself to 12 stages: 5; 21, 22, 23; 26 ÷ 33. Typical variant design allows studying technological processes and operation properties (excluding the physical implementation of the object) using a sketch model. This allows CAE tools, STEP standard and PDM-technologies, coordinated by PLM-system [3].

Figure 1. Spiral model lc

Output. The spiral model of the life cycle and PLM technologies are, in our opinion, the most effective combination of solving the assigned tasks, creating effective products (samples of new technology)[6]. 

Literature:

1. Жук К.Д. Системные методы в программировании жизненных циклов объектов новой техники. – В кн.: Автоматизация проектирования сложных систем. Минск: ИТК АН БССР, 1976.  С.16-26.
2. Жук К.Д. и др. Построение современных систем автоматизированного проектирования. – Киев: Наукова думка, 1983. 248с.
3. Основы автоматизации технологических процессов и производств: учебное пособие: в 2т.  Под ред. Г.Б.Евгенева. – Москва: Издательство МГТУ им. Н.Э.Баумана, 2015.
4. Моисеев Н.Н.  Математические задачи системного анализа. – М.: Наука. Главная редакция физико-математической литературы, 1981. – 488 с.
5. Юсупбеков Н.Р. Интеллектуальные системы управления и принятия решений. – Лекции. ТашГТУ.  Ташкент. – 2019.
6. Асранов Хабибулло Камолдин ўғли «Управление жизненным циклом вновь создаваемого изделия» https://7universum.com/ru/tech/archive/category/182