=Paper=
{{Paper
|id=Vol-3647/SemIIM2023_paper_8
|storemode=property
|title=Multi-Architecture Unified Modeling for Manufacturing Service Value Net System Design
|pdfUrl=https://ceur-ws.org/Vol-3647/SemIIM2023_paper_8.pdf
|volume=Vol-3647
|authors=Qianhang Lyu,Peng Qi
|dblpUrl=https://dblp.org/rec/conf/semiim/LyuQ23
}}
==Multi-Architecture Unified Modeling for Manufacturing Service Value Net System Design==
https://ceur-ws.org/Vol-3647/SemIIM2023_paper_8.pdf
Multi-architecture unified modeling for
manufacturing service value net system design⋆
Qianhang Lyu1,2,* , Peng Qi2
1
Department of Informatics, University of Oslo (UiO), Oslo, 0316, Norway
2
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430070, China
Abstract
The synergistic development of product after-market is an effective way for manufacturing enterprises
to extend their value chains. As a system architecture design formalism method, model-based systems
engineering (MBSE) provides capable support in the design process of complex systems. In this paper,
a cloud-based manufacturing service value net system is proposed to help manufacturing enterprises
coordinate with partners. However, in this cross-organization collaborative activities, experts with
different domain backgrounds are familiar with various system specifications and modeling languages,
which makes it extremely hard for related stakeholders to collaborate and conduct information interaction.
Therefore, this article presents a semantic modeling method of GOPPRR and unified ontology modeling
karma language to support different MBSE standards. The specific domain meta-models of manufacturing
service value net system are developed throughout the whole lifecycle process. MetaGraph tool is applied
to build meta-models and models. Karma codes with consistent semantics can be generated automatically
in real time no matter what modeling language is taken. Concretely, an instantiated modeling case was
created in the basic of developed meta-model library. This paper conducts ongoing research for system
design in the manufacturing service field, and the proposed modeling method also implies reference
significance for designing of similar systems.
Keywords
MBSE, value chain theory, semantic modeling, collaborative design, forward design
1. Introduction
The development trend of manufacturing industry has changed from the traditional mass
produce to the downstream maintenance service business process [1]. Manufacturing enterprises
create value by concentrating in post-market service of products [2], leading the equipment
production industry in the stage of “service-orient manufacturing”. Value chain focus on the
profit sources of production and operation in a company from the value flow perspective,
including a series of value-related activities [3]. The manufacturing industry based on value
chain theory commonly has the status of "value siloes". It is difficult for a single enterprise
to provide optimal services in multiple specific areas of expertise. Therefore, it is urgent to
establish a cooperative platform to help manufacturing industry transform from single chain
SemIIM’23: 2nd International Workshop on Semantic Industrial Information Modelling, 7th November 2023, Athens,
Greece, co-located with 22nd International Semantic Web Conference (ISWC 2023)
*
Corresponding author.
$ qianhanl@uio.no (Q. Lyu)
0000-0002-8974-393X (Q. Lyu)
© 2023 Copyright for this paper by its authors. Use permitted under Creative Cons License Attribution 4.0 International (CC BY 4.0).
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mode to collaborative mode [4]. The aim is to coordinate multiple entities to create and distribute
benefits, and support closed-loop feedback of information [5]. In this paper, a manufacturing
service value net system is proposed to provide personalized service solution schemes for
customers. This system integrates services of multiple subjects, including core enterprises,
parts suppliers, maintenance providers and logistics providers, adopting cloud platform as the
operation carrier which is described as manufacturing service cloud platform.
Business processes of manufacturing service cloud platform are extremely complex. It is It is
hard to implement system function definition. To this end, model-based systems engineering
(MBSE) has been proposed to tackle system complexity [6, 7]. MBSE technology can enhance
the integrity of system design by establishing system models to describe complex product
systems. It has already been studied and practiced in the field of aerospace [8, 9] and military
[10]. Therefore, a semantic modeling method of GOPPRR (Graph, Object, Point, Property,
Role, and Relationship) approach and multi-architecture unified modeling language karma
is proposed. GOPPRR basic elements are used as the foundation of modeling while karma
language is adopted to normalize the semantic description of the system.
In addition to the complexity of the system itself, the coordination of the system design process
is also difficult. On account of the different knowledge backgrounds of experts, supportive
technique tool is needed. MetaGraph, a multi-architecture unified modeling software, is applied
in this paper to meet the requirements of multi-team collaborative system design.
On the whole, in order to establish the proposed manufacturing service value net system,
a semantic modeling method is adopted. Based on GOPPRR theory and RFLP (Requirements
engineering, Functional design, Logical design, Physical design) forward design principle, it
provides distinct creation procedure of manufacturing service system. Moreover, the unified
formalism description of models is beneficial to semantic integration purpose, which improves
coherence and interoperability of different designer and developers. Additionally, the established
meta model library made direct contributions to instantiated system modeling.
The rest of the paper is organized as follows. Section 2 presents the literature review. In
Section 3, the manufacturing service value net system design problem is described and the
modeling methodology is illustrated. A case study conducted in Section 4 validates the proposed
method. Section 5 concludes the article.
2. Literature review
The design and development of complex systems has long been the focus of systems engineering.
Oriented by the classic V-model, its life cycle includes a top-down design process and a bottom-
up validation process [11]. User requirements are regarded as the core of forward design in
project management, promoting the availability after project implementation. Compared to
document-based systems engineering (DBSE) approaches, model-based systems engineering
(MBSE) can significantly improve coordination throughout design phases. The traditional mode,
in which each stage is carried out independently, involves a large amount of data and files and
has low tolerance for operational errors. Not only is the communication consuming high, but
also the reuse of experience and knowledge is inconvenient once design changes or system
upgrade iterations occur. However, although model-based systems engineering methods can
ease these problems, engineers still face barriers from modeling languages in building models.
In order to meet miscellaneous scenarios, there are several specifications and general modeling
languages of model-based systems engineering in academia and industry, such as BPMN [12],
UML [13] SysML [14], EAST-ADL [15], etc. However, most of the existing studies still cannot
meet the requirements of collaborative design across multiple groups. As an expression form
of the design content of the system, models contain the underlying abstract elements and the
detailed domain-specific information describing actual physical world. As the most powerful
graphical representation method, GOPPRR approach supports meta-model definitions in the
basis of abstract elements of meta-meta-models [16]. Therefore, this paper uses a semantic
modeling method based on GOPPRR to remove the ambiguity of the graphical descriptions,
which is helpful for designers familiar with different design specifications to understand each
in formal definition of meta models.
3. Modeling approach of manufacturing service system
As mentioned in Section 1, the current stage of service-oriented manufacturing means man-
ufacturing enterprises need to extend their value chains, and promote value synergy among
enterprises to create value innovatively. So as to offer customers more sophisticated service solu-
tions. This section introduces manufacturing service value net system in detail. We proposed a
karma-based semantic modeling method to construct concept model libraries for manufacturing
service value net system.
3.1. Problem statement
As mentioned above, it is urgent for manufacturing enterprises to upgrade from single product-
centered value chain mode to integrated customer-centered value net mode. The most important
thing is to improve the after-sales service of products. It comes the circumstance that one
equipment manufacturer (referred to as a core enterprise in this paper) cannot provide complete
post-sales service. This paper carried out inter-enterprise business coordination on a centered
platform by virtue of the integration of value chains.
Requirements of customers’ needs can be described in two different after-sales service sce-
narios: 1) equipment products are still in the warranty period; 2) or beyond the warranty period.
In former scenario, core enterprises always provide full warranty service. The department
responsible for after-sale service immediately respond to the customer’s request for repair and
provide corresponding maintenance service or material allocation. As for the other situation,
the enterprise is not solely responsible for the operation failure, but the participation of core
enterprise can bring considerable benefits to itself and customers. Enterprises can collect more
operational quality information and operational status data. Customers can also get more
professional service solutions schemes. In the meantime, material suppliers and maintenance
service providers join to stimulate the diversity and competitiveness of the post-product market.
Thus, it is up to the user to choose different system functions, such as fault diagnosis only or
several of system function. In addition, users can also freely choose partners with different roles,
for example, with maintenance service providers, or just coordinate with material suppliers to
deliver parts.
Based on the above scenarios, the manufacturing service value net system proposed in this
paper includes three main functions: fault diagnosis and residual life prediction, after-sales
market service and material allocation. The stakeholders involved include customers, core
enterprises, maintenance service providers, material suppliers, logistics providers and cloud
service providers. Detailed system business process design is introduced in Section 4.
3.2. Overview of semantic modeling method
Based on two above mentioned scenarios, main functions and business processes can be defined
for manufacturing service value net system designed for a specific platform named manufac-
turing cloud platform. According to the principles of forward design methods, RFLP theory
is adopted and a semantic modeling method is proposed. Aiming at the features of domain-
specific modeling for complex system design, the graphical system models are constructed
through GOPPRR approach combined with a third-order framework which is comprised of
meta-meta-models, meta-models, models and instantiated conceptual models. Moreover, in
order to support co-design across multiple groups, karma, taken as a unified modeling language,
can describe conceptual models of the system under the same semantic and syntactic structure.
The overview of the research methodology is shown as Figure 1.
Before developing conceptual models for project design, requirements model, functional
model, logical model, and physical model, take RFLP theory as the system architecture design
principle. As shown in Fig. 1(a), requirement analysis is carried out against the background of
actual service scenarios to analyze and capture the needs of stakeholders. Functional framework
is defined oriented from requirements, and system functions (overall systematic functions and
subsystem business processes) are planned based on technical support (e.g., cloud platform
infrastructure). In addition to the business logic of the key functional subsystems, the logical
interactions between blocks, or between a block and a stakeholder are also considered to
describe system behavior in the logical design. Finally, the physical architecture of the system
can be determined, including physical configuration, subsystem structure, as well as detailed
description of components.
Karma language is a semantic language with consistent textual semantics and syntax across
different modeling languages. In other words, whatever modeling language used by system engi-
neers in any field can be formalized into consistent descriptions under this uniform specification.
For cross-team system design barriers, a multi-architecture modeling tool, MetaGraph, is applied
to construct system models. It supports meta-model definition based on meta-meta-models, and
all stakeholders can edit the meta-model in the tool according to their domain expertise, which
provides good scalability for the method proposed in this paper. Furthermore, code generation
function of MetaGraph supports the karma ontology transformation of system models, solving
the problem of heterogeneity in the process of cross-organization system design.
4. Case study
It is particularly beneficial to adopt MBSE method for modeling analysis when designing
complex systems. This section verifies the feasibility and necessity of proposed semantic
modeling method during system operation and development. Fig. 2 shows a comprehensive
Figure 1: Semantic modeling method under RFLP principle
overview of this case study. Aiming at realizing the value extension of post-market service
for large manufacturing enterprises, the business collaboration process workflow of relevant
stakeholders under industrial scenario is presented. For the purpose of scientifically expressing
this system, the manufacturing service value net system instance models are developed using
meta-model library based on RFLP process. Meanwhile, the unified karma language formalism
is given for all kinds of concept model files. All models are defined and constructed in the
MetaGraph.
4.1. Business process workflow of manufacturing service value net system
As described in Section 3, the system consists of three key functional subsystems (shown in
Fig. 2(a)). The first is represented as Faulty Diagnosis and Residual Life Prediction Subsystem,
including faulty diagnosis component and residual life prediction component. The fault diagnosis
component executes online diagnosis to get fault modes and maintenance suggestions according
to customers’ requests. Only fault symptom information is needed by users while using. The
residual life prediction component generates product lifecycle curves according to the state
detection data to estimate whether the product is in a safe operating period. In this way, when
operation failure is about to occur, early warnings are attainable, so that materials can be
scheduled in advance in coordination with the material allocation function to speed up the
response. The Aftersales Market Service Subsystem defines the after-sales service delivery
modes for different contexts. If the fault occurs while the product is still under warranty, all
maintenance services are provided by core enterprises. According to the warranty policy, if the
core enterprise does not assume the maintenance responsibility when the fault occurs, customers
only need to publish the repair information on the platform. Moreover, the After-sales Market
Service subsystem supports different users to call platform functions on demand, recommends
the optimal maintainers and coordinates with material configuration. The Material Allocation
Subsystem handles orders based on material requirement forecasting function component. In
addition to this basic function, it should also support warehouse inventory optimization through
the material configuration situation, thus to generate the optimal material scheduling scheme.
This design of function can effectively alleviate the problem of material idleness and reduce the
cost under the premise of ensuring the timely supply of materials.
In the maintenance service scenario described in this paper, the customer first releases the
service requests and interacts with partners in the order processing interface through the
After-sales Market Service subsystem. According to the reported fault phenomenon, the Fault
Diagnosis subsystem is designed to obtain diagnosis results, which is used as the basis to
issue material requirement orders. Then, the After-sale Market Service subsystem triggers the
Material Allocation subsystem to generate configuration schemes. Through the abovementioned
business processes on the manufacturing service value net system, maintainers can directly
provide maintenance services on site and obtain feedback from customers.
4.2. Semantic modeling process of proposed system
In this case study, the semantic modeling process is presented in Fig. 2(b). The first step of
the system design is the requirement definition based on the requirement scenario. Oriented
toward customer demands of actual manufacturing practice is a vital principle. Items in Re-
qIF (Requirements Interchange Format) and requirement diagram are used to systematically
illustrate requirement analysis, and the stakeholders are defined using the scenario use case
diagram. Functional analysis includes a comprehensive activity diagram of the manufacturing
service value net system, as well as functional descriptions and functional use cases for each key
functional subsystem. Logical analysis regulates the interaction process among stakeholders
and system components. The following four interaction processes are represented by sequence
diagrams: purchasing interaction process; interaction process between residual life prediction
Figure 2: Instance modeling through proposed semantic method under system scenario
component and Material Allocation subsystem; information interaction of lifeline objects in
the maintenance service provision within warranty; and information interaction of each object
in maintenance service provision out of warranty. Thus, the physical structure of the system
can be constructed. In this case, block definition diagram is used to express the composition
relationship of subsystem modules and component modules. Combined with the advanced
decomposition display of technical tools, the physical decomposition diagram of components
can be shown simultaneously in the same page as a sub-diagram of the whole system structure.
System structure design process also defines the Docker form of deployment mode on the
proposed manufacturing service cloud platform.
5. Conclusion
In this paper, a manufacturing service value net system is proposed to raise the benefits from
aftersales market of manufacturing companies, and a GOPPRR approach is adopted under RFLP
design principle to construct a theoretical framework through a proposed semantic modeling
method for collaborative designing. A multi-architecture modeling language named karma is
used to formalize models built by manufacturing service value net model library. In order to
demonstrate the practical operability of the method, instantiated models are conducted in an
MBSE tool. In the meantime, feasibility is also verified by the case study. The contributions
provided in this article support a strong foundation for the design process in this specific domain,
and offer inspiration for development stages of other similar complex systems.
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