=Paper= {{Paper |id=Vol-2413/paper18 |storemode=property |title= Enterprise Product and Service process Design with the Use of Intelligent Technologies |pdfUrl=https://ceur-ws.org/Vol-2413/paper18.pdf |volume=Vol-2413 |authors=Yury Telnov }} == Enterprise Product and Service process Design with the Use of Intelligent Technologies == https://ceur-ws.org/Vol-2413/paper18.pdf
     Enterprise product and service process design with the
                 use of intelligent technologies 1

                                  Yury Telnov 1[0000-0002-2983-8232]
                  1
                      Plekhanov Russian University of Economics, M oscow, Russia
                                      Telnov.yuf@rea.ru



          Abstract. The article addresses methods of designing product and service pro-
          cesses in digital transformation conditions allowing for customized production in
          accordance with dynamically changing user demand.
          We consider the use of the model based enterprise concept for product lifecycle
          management for integrated presentation and use of related data on shared assets
          as a methodological basis for the design of product and service creation pro-
          cesses. M ethods of designing such processes on the basis of service-oriented or-
          ganization of interaction of business partners in the network environment using
          the tools of network-centric approach, ontological engineering of the domain and
          interaction of intelligent software agents using microservices are proposed.
          To construct a service-oriented configuration of the processes of creation of prod-
          ucts and services, the value chain is considered, in which the individual links of
          value formation are investigated for compliance with the capabilities of possible
          partners of network interaction within the network enterprise.
          For the organization of effective network interaction of all stakeholders in the
          framework of joint activities to create products and provide services, ontological
          modeling of the business model is proposed from the standpoint of formalization
          of key values, competencies and capabilities of the enterprise and its partners,
          business processes and necessary resources.
          Engineering of intelligent software agents is carried out on the basis of domain-
          driven design methods, which allows for contextual analysis of the functions per-
          formed and determine the boundaries of the microservices that implement them.
          The proposed methods of ontological engineering and microservice organization
          of interaction of intelligent agents provide effective digital engineering of creat-
          ing products and services of service-oriented enterprises.

          Keywords: Product and Service Process Design, M odel-Based Enterprise, Ser-
          vice-Oriented Architecture, Ontology-Based Domain Engineering, M ulti-Agent
          Technologies.




1
    The research was financially supported by the Russian Foundation for Basic Research (RFBR),
     project 19-07-01137 А

Proceedings of the XXII International Conference “Enterprise Engineering and Knowledge M an-
agement” April 25-26, 2019, M oscow, Russia
1      Introduction

The use of modern digital technologies within the Industry 4.0 framework drastically
changes the nature of product and service design, production and distribution processes.
On the one hand, products and services are endowed with engineering software com-
ponents ensuring flexible construction of necessary production and business processes
within the Internet of Things concept, on the other hand, the products and services are
represented in the informational space as digital models, which are used throughout all
stages of the design, production and distribution lifecycle. Digital models are also used
to represent production and business processes, which are increasingly implemented in
the form of business partners networking. In this context the crucial research tasks are
then developing methods and tools for intelligent technologies application in creating
the concepts of products and services, flexible formation of innovative processes and
knowledge management at all stages of product and service creation, production and
distribution lifecycle in the conditions of dynamic enterprise networking structures evo-
lution in the Internet environment, which is nowadays included in digital engineering
concept with help of the model-based enterprise [1].
    The task of product and service processes design and implementation alone appears
to be quite difficult due to the necessity of engaging a multitude of cooperating contrib-
utors interested in the end result: manufacturers, suppliers, contractors, users. This in-
curs increased significance of integrating multiple knowledge sources and ensuring
their availability in various contexts through the support of a unified model of product
and corresponding processes, which makes it possible to manufacture products and ren-
der services according to customized orders. Integration here is viewed both vertically
– to create value-added chains: user – manufacturer – supplier, and horizontally – to
form common pools of manufacturers’ (suppliers’) resources for common use within
the so-called ‘shared economy’ concept. In both integration aspects, taking into account
the industrial Internet capabilities, the role of the manufacturer as the system integrator
in the service business model of all stakeholders interaction and respective support of
digital model of product and associated processes at all lifecycle stages increases .
    The key problem of product and service processes digital engineering is then com-
puter support of a unified Model Based Enterprise during all stages of product or service
lifecycle: formation of a concept, development, design, manufacturing, release and sup-
port. Here the problems of continuous model-based system engineering of requirements
and check-up of their executability over the course of innovative project evolution come
to the fore. Within this framework the modelling process is not separated from the prod-
uct design and development process, waterfall development of a product or service is
fully replaced by the iterative and spiral engineering technology, and the knowledge
management process becomes continuous at all stages of the lifecycle.
    In order to align this data between various systems within the product lifecycle a
digital thread concept is being developed today [2]. This approach is characterized by
integrated representation and use of linked data on shared resources (assets), which are
considered from different functional points of view, throughout the whole lifecycle of
products and services. The most attractive research areas for the development of this
concept are related to the use of approaches based on domain -driven design, micro -
service and multi-agent organization of sys tem support, ontology-based engineering,
which are analysed in this article. The article is aimed at revealing the most forward -
looking methods of designing product and service processes on the basis of intelligent
technologies.


2      Research Methodology

Design of innovative product and service processes of enterprises is premised on the
extensive employment of knowledge management methods. Reputed classical papers
in the sphere are the works by I. Nonaka and H. Takeuchi [3], P. Senge [4], T.A. Gav-
rilova and V.F. Khoroshevsky [5], V.B. Tarasov [7] etc. Those papers pay great atten-
tion to the problems of developing an innovative knowledge creation and distribution
technology, systematizing information sources on the basis of enterprise ontology, or-
ganizing collective work and self-learning in project teams. Particularly the problems
of products and services design are studied in the papers devoted to product lifecycle
management (PLM). For example, product lifecycle management, which can be used
as a basis for building well-organized value chains with participation of boundary part-
ners, is sufficiently fully reflected in the so-called CALS technologies [6], where one
of the key roles is played by the product data management (PDM) module.
    The existing PDM systems heavily focus on product structure representation and
management of configuration versions, as well as on integration with other components
of the lifecycle management and computer-aided design system. Unification of contents
construed as unambiguous correct interpretation of data on the specific product at all
stages of its lifecycle is achieved by developing application meta descriptions secured
in CALS application protocols. Unification of lists and names of entities, attributes and
relations in certain domains is the basis for uniform digital description of a product in
the informational space. Product components may be linked to various design docu-
ments and documents related to marketing, procurement, planning, administration etc.
These documents are mainly reference materials from the knowledge management
standpoint. At the same time from the standpoint of product manufacturing and service
provision feasibility and efficiency analysis automation there is an obvious lack of in-
formation. Besides, the PDM system is good to be used at the stage of design and sub-
sequent manufacture of products and services, when the project has already gained a
reasonably fair image. The use of model base enterprise (MBE) method [1] allows in-
tegrating process design and implementation with the feedback on the effectiveness of
resulting design solutions.
    At an earlier innovative stage of project studies, where the success of business is
actually laid down, there is a requirement for a bigger volume of knowledge with regard
to the defined value characteristics of products and services, risks and resource capaci-
ties of their marketing, value chains (business processes), used resources and activity
agents, systematized in the form of enterprise ontology [8,16,17]. From the perspective
of revealing high-potential characteristics of products and services forming their con-
cept it is necessary to highlight the papers on knowledge extraction from large volumes
of digital and text data, reflecting market demand and supply, status of research and
technologies [9], as well as papers on cognitive formation of new concepts [10-12].
   Building value-added chains in line with the designed products and services is inter-
twined with the problem of business model selection, which become more flexible and
versatile in the conditions of digital technologies utilization, most notably cloud-based
and microservice technologies [13-15]. Business model selection primarily depends on
the ontological description of a conceptual model, which are introduced in the papers
by A. Osterwalder [16] and J. Dietz [17]. Methods of conceptual domain modelling and
subsequent design are developed today in the domain -driven approach to system design
[18, 19]. Effective distribution of value-added chain contributor roles both within the
enterprise and between the partners of a network enterprise is usually premised on the
use of multi-agent systems [20, 21]. At present a network-centric approach is rapidly
developing, based on the principle of co-evolution of self-organizing systems [22, 23]
and solving the tasks of resource distribution, planning, optimization and real-time fol-
low-up within the framework of recursively deployed self-organizing network of multi-
agent planners.
   The methods described can be used as a basis for building an integrated methodology
of product and service processes design with the use of intelligent technologies.


3      Research Results

3.1    Methods of Enterprise Service-oriented Architectures

In the sphere of enterprise service-oriented architecture development formation of en-
terprises more freely linked to each other and cooperating in order to achieve fluctuat-
ing but articulate goals and implementing service interaction procedures gains in im-
portance. Solution of this task is facilitated by the wide use of digital technologies and
Internet environment making it possible to create network enterprises. A network en-
terprise is an enterprise functioning in the global Internet environment and formed by
means of dynamic interaction of joint production activity contributors on the principles
of service implementation of demand for products and services. The demand also has
digital representation, in the same way as the products and services, and dynamic inter-
action of network business process actors should ensure taking real-time business de-
cisions upon enquiry or opportunity.
   It is proposed to base the service-oriented configuration of business process es on a
value chain built so that each link executes certain type of activity to form this or that
value of a finished product or service. Value creation necessity and possibility are eval-
uated from the strategical point of view, whereas from the tactical and operative view-
points specific value chain configurations are built, where individual types of activity
can be performed by different manufacturers depending on their level of competence.
The interaction between two boundary executors in the value chain is based on the
“Order Placement” – “Service Provision” principle, and in the network environment
such interaction is performed by means of software services. This results in the emer-
gence of new forms of value chains, such as innovative value chains with non-repeating
product manufacturing and service provision technologies, as well as in value networks
widely using integrated knowledge source management in a certain area of activity .
   The main principles of service-oriented architecture of a modern network enterprise
are:
   - Support of continuous heavy use of knowledge of the products /services being de-
signed. Acquisition and management of knowledge of the product (service) and its
components, as well as of the working processes required to create it.
   - Support of the client model and its requirements to the product/service being cre-
ated. Multi-aspect client model represents the enterprise knowledge of the current and
long-range values of the client, product demand and quality criteria.
   - Support of dynamic business process formation. Acquisition and mana gement of
knowledge of parties’ interfaces – mandatory interactions of various contributors dy-
namically forming a common network business process, where the parties are in the
“Customer – Supplier” relations.
   - Rise of the knowledge expert role in knowledge acquisition and support in the uni-
fied knowledge database. In the process of knowledge collection and structuring
knowledge experts get informational and analytical support from the knowledge -based
intelligent system services.
   - Open architecture of a knowledge-based intelligent system. Expandability of the
imperative and declarative knowledge system, of methods and services for dynamic use
of capabilities gained at other projects.
   - Controlled modularity. Loosely coupled architecture of its components formed on
the basis of relatively independent principles, methods, pieces of knowledge and mod-
ules of other types.
   - Support of various forms of knowledge representation. Informal and formalized
representations of knowledge are integrated using sematic ontology network.
   - Use of knowledge to solve production tasks. Integrated enterprise knowledge is
used in solving of the widest range of production tasks, in particular, in execution of
quality walkthroughs at various stages of design, component manufacture, p roduct as-
sembly and testing.
   Consruction of an enterprise service-oriented architecture is performed at three lev-
els: strategic, tactical and operative [21]:
   - The strategic level solves the task of defining and developing key enterprise com-
petences (types of activity) that significantly influence its position on the market. Over
the long term the key competences (types of activity) develop into a system of strategic
product and service production plans, for which targets and measures to achieve de-
signed values are set.
   - The tactical level solves the task of defining a set of business processes in the value
chain, which in accordance with key competences (types of activity) and critical suc-
cess factors are performed either by the enterprise itself or outsourced to partners, where
outsourcing is performed dynamically similar to competence development . Such value
chain is based on a selectable business model integrating a set of different business
processes.
    - The operative level in accordance with key features of the selected business model
and key performance indicators, as well as specific unfolding and ever-changing situa-
tion in the business environment, solves the task of configuring online business pro-
cesses. Business process execution monitoring results in the accumulation of real sta-
tistics, which is used to update the business model with regard to selection of its specific
components.
    To solve the above mentioned enterprise service-oriented architecture engineering
tasks it is reasonable to use and develop intelligent technology methods and tools:
    - ontology engineering resulting in building of an ontology, which makes it possible
to structure and handle a domain model: objectives, processes, resources, organiza-
tional structures at various level of representation (strategic, tactical, operative), jump-
ing between them in order to detail and specify scheduled activities.
    - multi-agent technologies handling generation of effective dynamic interactions of
intelligent agents in the product and service business processes of network enterprises .


3.2    Domain Ontology Engineering Methods

The proposed main method for developing a knowledge-based intelligent system for
network enterprise product and service processes design is domain ontology engineer-
ing, which ensures effective interaction of all interested joint activity contributors in
the informational space. In this context domain ontology implements the possibilities
of collective business processes design on the basis of:
   - on-demand dynamic engagement of clients and experts from the enterprise ecosys-
tem;
   - rapid integration of agents as subcontractors and partners into dynamically gener-
ated business processes;
   - integration of expert agents representing different domains into one multiprofes -
sional team;
   - support of semantic interoperability of systems within the integrated business pro-
cess being generated.
   Ontology-based domain modelling implies formalization of the enterprise key val-
ues and competences, resource and technological capabilities of th e enterprise itself and
of its partners in this or that activity, which are represented in the form of an integrated
business model. Thus domain ontology ensures representation of knowledge:
   - for the top management to make decisions on creation or transfo rmation of new
types of products and services.
   - to design or upgrade the existing types of activity used by system analytics, enter-
prise architects, developers, project managers.
   - for the interested parties to be informed about new projects and possibilities of
creating network enterprises .
   The proposed methods to form the key features of products and services are the
methods used for processing large volumes of data allowing analysing open infor-
mation from various sources by means of data and text analysis methods. For cognitive
understanding of extracted knowledge it is supposed to use methods of automated for-
mation of concepts and categories. For taking a collective decision on giving key value
signs to products and services it is supposed to use the network-centric approach allow-
ing finding well-considered solutions with account of uncertainty factors and risks .


3.3    Methods of Creating Multi-agent Technologies Constructing Effective
       Dynamic Interactions of Intelligent Agents

The most effective method to generate network structures of product and service busi-
ness processes is the use of multi-agent technologies that make it possible to formalize
distribution of roles of main value chain agents. The proposed mulita-gent intelligent
system design methods are the methods of domain-driven design based on the princi-
ples of contextual analysis of performed functions, allowing marking the boundaries of
microservices for individual executors and their software implementation [22, 23].
Thus the original value chain may be updated from the perspective of rational organi-
zation of information exchange and performed operations. Multi-criteria analysis of al-
located microservices with the use of soft computing provides for the possibility of
distributing executed micros ervices by executor agents and building an effective multi-
agent system.
   From the software implementation point of view intelligent agents own a set of mi-
croservices carrying out query construction, monitoring of their executability, business
process selection and configuration, their execution, follow-up, response to exceptional
conditions. Transaction status is represented in the dynamic database available to net-
working agents. The knowledge database contains sets of decision rules applied de-
pending on the domain specific features .
   In this respect interacting intelligent software agents take decisions on the basis of
knowledge database of business partners economic health valuation rules using open
Internet sources:
   - Transaction initiator agent must maximize the value acquired from process execu-
tion by executor agents in respect of its project risks.
   - Ttransaction executor agent must minimize its resource capabilities deviation
against the requirements of transaction initiator.
   To perform dynamic analysis of executor agents servicing efficiency statistics (ex-
perience) of agents networking and emergence of problems in the data warehouse is
accumulated with subsequent processing by business analysis software (Business Intel-
ligence) and intelligent data analysis. This ensures continuous improvement of services,
early problem localization, diagnostics of causes and generation of recommendations
to improve business process components for the type of product or service in question.


4      Discussion

As a route forward for product/service process engineering methods we should high-
light the tasks of standardization of methods and protocols facilitating analysis of prod-
uct, process and logistics models interfaces by integrating knowledge of specific do-
mains and knowledge in the sphere of system engineering. Special emphasis is placed
upon solving the problems of metrics of conformance evaluation between the require-
ments and the realistic possibilities of product manufacturing and service provision. It
is also very important to refine design solution visualization tools, which simplify in-
teraction of all interested business process contributors, as well as the possibilities of
generalization of business process reference models for their reuse.


5      Conclusion

Usage of the proposed enterprise product and service process design methods on the
basis of enterprise service-oriented infrastructure, ontology engineering and micro -
service-based organization of intelligent agent interaction is aimed at building an effec-
tive configuration of joint activity contributors networking, which allows quick adap-
tation of software and organizational components to varying market conditions and re-
quirements.
    Ontology-based domain modeling ensures integrated approach to building a concep-
tual domain model, which progressively evolves throughout all stages of the prod-
uct/service lifecycle and supports continuity of requirements engineering and executa-
bility monitoring in the constructs of products and services and respective business pro-
cesses.
    Usage of domain-drive design, microservice-based organization of intelligent
agents’ interaction technologically implements the principles of customized production
of products and services in the modern enterprise digital engineering.


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