=Paper=
{{Paper
|id=Vol-1300/paper9
|storemode=property
|title=How Model-Based SE Makes Product/System Lifecycle Management Framework More Effective
|pdfUrl=https://ceur-ws.org/Vol-1300/ID09.pdf
|volume=Vol-1300
|dblpUrl=https://dblp.org/rec/conf/ciise/TommasiV14
}}
==How Model-Based SE Makes Product/System Lifecycle Management Framework More Effective==
https://ceur-ws.org/Vol-1300/ID09.pdf
INCOSE Italian Chapter Conference on Systems Engineering (CIISE2014)
Rome, Italy, November 24 – 25, 2014
How Model-Based SE Makes Product/System
Lifecycle Management Framework More
Effective
Carmelo Tommasi
Atego Systems Italy
Via Tobagi 18
20068 – Peschiera Borromeo (Milan, Italy)
carmelo.tommasi@atego.com
Eugenio Vacca
Business Transformation Manager
PTC, Inc.
C.so Unione Sovietica 612/15/C
10135 – Torino – Italy
evacca@ptc.com
Copyright © held by the authors.
Abstract. Product Lifecycle Management business approach goals have always been
key to foster product innovation and companies’ competitive advantage through
effective Intellectual Property creation, evolution and reuse management to
successfully transition into successful product manufacturing and operations, taking
into account the whole product lifecycle and its evolution through changes or derived
products creations. Over the past few decades we went through several shifts in forces
driving product development, from product digitization, to globalization, to
regulation, to personalization, to servitization, to software intensive products, to
connectivity increasing the complexity of the products, the processes required to
develop, manufacture, operate, maintain and retire them, the amount of information
and relationships between information to manage. Moreover a product can now be
described as a complex system itself, or part of a bigger system or even part of a
System of Systems, leading to an even grater complexity to manage in order to be sure
that the initial requirements or needs are met by the product or system when it starts
operating. This paper aims at showing how a Systems Engineering and Model Based
Systems Engineering approach can complement and add value to a Product/System
Life Cycle Management solution framework in order to improve the capability of an
organization to meet initial requirements/needs on time and within budget.
Introduction
Intellectual Property is the asset allowing a company to be more competitive and
successful in today's increasingly knowledge-based economy. It is all about value
generated by a Company, in fact IP normally cannot be showed on the corporate
balance sheet as an intangible asset, but its value determines the success or a failure of
a business, being Managers' ability to exploit these effectively and turn them to a
profit, so IP can affect the price of the stock.
IP can include many items, such as Patents, Proprietary Technologies, etc. but,
overall, include the skills, the knowledge and all relevant data that a company has
developed about how to build its products/product lines or services; the contributions
come from individual employees or groups.
Maintaining, increasing and extracting value from intellectual property and
preventing others from deriving value from it is an essential responsibility for any
company.
Initially, IP was managed mainly through paper based documents and processes, such
as requirements, specifications, drawings, etc. verified and approved through hand
written signatures, then in the mid ‘80s a first wave of transformation in the
manufacturing industry led to the product DIGITIZATION, the IP was transformed
from paper and physical assets to digital assets, replacing analog product and service
information with a fully accurate virtual representation that can be easily leveraged
across the value chain (engineering, factory floor, service) and starting an evolution
which went though several other transformations up to the present days.
Figure 1. Waves of manufacturing transformations
Following the digitization transformation we went through 6 additional waves of
evolution:
1. GLOBALIZATION
The general shrinking of the world driven by technology that eliminates economic and
geographical divisions and opens new markets.
2. REGULATION
Enforcement of governmental rules, non-governmental organization policies and
industry standards related to environment, health, safety and trade.
3. PERSONALIZATION
Efficiently tailoring products and services to accommodate regional and personal
preferences.
4. SOFTWARE-INTENSIVE PRODUCTS
Integrated systems of hardware and software capable of sophisticated
human-to-machine interaction, diagnostics and service data capture, with additional
value delivered through enhancements.
5. SERVITIZATION
Fundamental business model shift in which products evolve to integrated “bundles” of
services capable of delivering new value continuously throughout the customer
experience lifecycle.
6. CONNECTIVITY
Pervasive networks of “things” – often mobile – embedded with sensors and
individually addressable to enable sophisticated monitoring, control, and
communication.
Alongside the evolution waves a disciplined approach and supporting tools emerged
to manage the lifecycle of products and the information created and consumed along
the lifecycle, this approach and tools are recognized with the name of PLM or Product
Lifecycle Management.
The components of an effective PLM framework, able to effectively support
manufacturers across the transformations, have extended the original classical PLM
and CAD (Computer Aided Design) domains to SCM (Supply Chain Management),
ALM (Application Lifecycle Management), SLM (Service Lifecycle Management)
and IoT (Internet of Things) domains, as show in Figure 2.
Figure 2. Extended PLM framework
Each step in this evolution also brought with it an increased complexity in products
and systems definition as well as related IP management, leading to increasing
difficulties in getting the right products to the market, on time, within budget and at
the right price point.
How can organizations cope with this increasing complexity of today systems, in a
scenario where the market asks not just for products but also for configurable products
and services? The solution is augmenting the Extended Product Lifecycle
Management framework, to transform it into a collaborative, multi-disciplinary
Systems Engineering practice through the adoption of a fully embedded Model-Based
Systems Engineering methodology.
Of course, this makes sense especially for complex products, and allows formally
describing and designing a system since the start of requirements analysis phase.
For the scope and objectives of this paper, we will analyze the components involved in
the management of the system definition process and information, describing the
positive impacts of adopting a MBSE/PLE approach to System Development.
Content
We will introduce the objectives of Manufactures in current market context and will
explain how the new Model Based approach extends the traditional PLM and Systems
Engineering vision.
Then we will talk about our guiding principles and the 4 Systems Engineering vision
cornerstones and will highlight that technical approaches on this extended Systems
Engineering vision need to be driven by industry, mainly the mission and safety
critical, embedded system industry.
Manufacturers’ Objectives and Engineering Challenges
Today, as organizations struggle to produce more innovative products in the context
of the transformations the market went through, undoubtedly, they will continue to
increase the amount of software within those products, which will further drive
complexity at levels much higher than before, especially taking into accounts the tight
requirements about safety imposed by national and international regulations.
Organizations have driven significant improvements in the way they engineer and
deliver those products in order to address these trends. A key area for improvement is
fostering a transformation from isolated systems, hardware, and software engineering
disciplines to a collaborative, multi-disciplinary engineering practice, that begins with
product requirements and continues throughout the lifecycle, conveying the following
set of engineering challenges:
Ensuring customer needs are met
Reducing and mitigating program/product risks
Increasing reuse while supporting system/product variants
Understanding trade-offs between and across needs, requirements and system
performances
The most suitable way to confront those challenges for complex, safety critical
products and systems is a disciplined approach such as Systems Engineering.
However, traditional Systems Engineering frameworks, as the one described by the
popular V-Model portrayed in Figure 3, are incomplete, missing important elements,
which require system design activities in order to “enable the realization of successful
systems” and to support all waves of manufacturing transformations. We defined and
propose a reference framework aiming at supporting the Total System Lifecycle
Management, enabling true whole life support.
Figure 3. Traditional Systems Engineering framework
System Lifecycle Management
Figure 4 illustrates our proposal for the Extend Systems Engineering and Lifecycle
Management framework, where the traditional Software, Mechanical and
Electrical/Electronic disciplines are complemented by the Manufacturing and Service
planning streams, which become part of the concurrent engineering process under the
control of the Systems Engineering methodology.
Figure 4. Extended Systems Engineering and Lifecycle Management
framework
The framework extends its coverage to the manufacturing, operations and in-service
phases of the lifecycle (up to the retirement, if needed) taking advantage of the
possibility to connect smart, software enriched products through sensors gathering
product and surrounding environment parameters or through actuators, enabling the
possibility to monitor, operate and service smart products remotely, and, in some
cases, enabling products to self-heal or self-adapt to operating conditions.
In the Extended Systems Engineering framework we move the manufacturing
planning and service planning processes upstream, so that organizations are in a better
position to deliver on-time and on budget, considering as early as possible the impacts
of design decisions on downstream processes.
For many organizations, Manufacturing and/or Service activities are outsourced or
carried on by separate legal entities; nevertheless, they must be considered highly
integrated processes to allow for optimal system performances design across the
lifecycle. Like for traditional concurrent engineering activities involving software,
mechanical and electrical/electronic components of the product organizations must
empower and support collaboration across geographical dispersed teams for
manufacturing and service planning and execution teams, also.
Like the traditional V-Model SE framework, the Extended Framework supports a
process involving decomposing the systems into subsystems and components and
guides through the flow of requirements analysis, system/subsystem/component
design, development, integration and test.
Within this framework Model Based Systems Engineering is of uttermost importance
during the requirements management and system architecture definition phases, also
enabling very early stage system simulation activities, allowing to analyze and take
best possible decisions about functional, RAMS (A. Garro, A. Tundis, 2012) and
performance requirements trade-offs.
Moreover, the use of a MBSE approach enables practices such as Set Based Design,
being adopted, for example, by the U.S. Navy for complex systems acquisition
programs such as the Ship-to-Shore Connection (SSC), to increase the chances to
define an optimal system solution for the required capabilities (D. J. Singer, N.
Doerry, M. E. Buckley, 2009).
Benefits and contribution of MBSE extends to the verification and operation phases of
the System Lifecycle, allowing to define Verification and Validation procedures as
well as formally describing operating procedures and supporting training activities
(Friedenthal, Sanford et al. 2007)
MBSE-Enabled Extended Framework
To successfully enhance the Extended Systems Engineering and Lifecycle
Management framework with MBSE methodology and overcome Manufactures’
engineering challenges 4 elements are the cornerstone of an effective solution and
must work together seamlessly, integrating the processes, the people – with related
organizations – and the technologies enabling the automation of process and
facilitating the activities of systems engineers and other participant roles in creating
and managing the product information and their relationships throughout the System
Lifecycle. These cornerstones are shown in Figure 5 and detailed in Figure 6.
Figure 5. The 4 cornerstones for an MBS-enabled PLM framework
overcoming Manufacturers’ engineering challenges
1. Model-Based Systems Engineering. This is obviously one of the components and
it is meant to manage the System Architecture and the UML/SysML/UPDM Model
methodology in a collaborative way, supporting a multi-user, multi-location model
authoring and sharing, even among geographically dispersed design teams. Thanks to
the common repository a full consistency is ensured, providing enterprise visibility to
functions, interfaces and all model elements with their relationships. A real-time full
traceability is a key element for an error-free model design.
2. System Requirements and Validation. Customer needs are elicited early in the
development cycle and come from different sources, like external requirement
management tools, general-purpose tools like MS Word or MS Excel, etc. Through
this framework component, it is possible to import external requirements from the
most common formats (ReqIF, MS Word, Excel, etc.), and then analyze, decompose,
detail, trace them through system development. It is also key to enable the continuous
validation of lifecycle assets from requirements to test as they are created and changed
and verify as-designed and as-built product against requirements and validate it
actually meets initial needs throughout operations.
The adoption of a MBSE approach improves this component allowing the creation of
a link between unstructured, informal requirements and a formal, suitable for
simulation, definition of the same requirements.
Moreover MBS enable system engineers to formally define system requirements and
performance targets from high level needs, creating a early formal view of the solution
domain, directly linked to the problem domain which may be described informally.
Another added value of MBSE for the Systems Engineering and Validation
component is the capability to design and document early test cases and allow to
define and simulate system components’ behavior to start verification activities very
early in the development cycle, thus allowing for maximum efficiency in analyzing
performances and requirements trade-offs easily enabling early analysis of multiple
solutions at once.
Figure 6. Content of the 4 cornerstones
3. X-Disciplines Coordination. A complex system is made up by the means on
different disciplines: mechanics, electromechanical, electronics, software, etc. Being
extremely successful and effective in one discipline and lousy in the others lead to less
then optimal system performances and, possibly, to failure. It is key to take advantage
of high value collaboration between mechanical, electrical & software as well as
manufacturing and service engineering to be fully successful in designing complex
systems across multiple disciplines and interchange all the data in an easy, error-free
way.
Collaboration must be ensured also in order to control the system configuration as it
evolves through changes requested by participants in the system development
process, such as marketing, manufacturing, customer or design, tracing the change
process and evaluate their impacts on system quality, services, functions and
interfaces, as well as enable cost impacts estimation on system TCO (Total Cost of
Ownership).
MBSE enhances this component improving the ability to easily correlate:
the needs and requirements
the functions and related behavior
the interfaces
the physical structure
creating a bridge between a usually highly unstructured and informal definition of the
system (needs and requirements) and a very formal and structured description (the
product structure an related information needed to describe it, build it, quality control
it, etc.) and keeping those relationships up to date throughout system modifications,
facilitating change impacts analysis and reducing errors discovered at late stages of
development.
4. Product Line Engineering. Mass customization and best matching different
solutions for the same class of problems require the capability to reuse as much as
possible existing subsystems, components and engineering artifacts as well as manage
product platforms and product lines, optimizing the costs in order to satisfy multiple
needs with matching product and system variants.
The possibility to identify from the start the commonalities and develop at once
multiple versions of the same system, defined by a set of options and rules based on
option choices, for all disciplines is fundamental in order to govern the amount of
information needed to define, design, manufacture, test, operate and service all the
possible variants in an efficient way.
The use of formal, modeling, methods, such as OVM (Orthogonal Variant Modeling)
from PALUNO – The Ruhr Institute of Software Technology, coupled with classical
PLM product configurators enable the possibility to manage the design and definition
of system variants across the whole lifecycle, allowing to define a set of choices
identifying a specific system variant and filtering all the relevant information for that
specific variant at once, including needs, requirements, functions, activities, tasks,
interfaces, software, physical design, build instructions, service manuals, etc.
These components, which are not exhaustive of the whole framework but are the most
impacted by the introduction of a MBSE approach, improve collaboration across
disparate and geographically/functionally dispersed design teams, shorten
development cycles, allow to achieve higher product quality, faster time to market,
and, overall, increased design reuse.
Conclusions
Development and operation of complex systems requires a disciplined approach.
Extending a traditional PLM framework through adoption of Systems Engineering
and Model-Based Systems Engineering methodologies multiplies its typical benefits
of increasing product quality, reducing Time to Market and increase the number of
successful product launches.
Analysts and researchers agree on Systems Engineering effectiveness and the value
added of Model Based Systems Engineering.
Boeing found that the most rigorous systems engineering practices applied to the most
complex system enables the completion of the project in ½ the time when compared
with the least complex system manufactured with the least rigorous systems
engineering practices. (E. C. Honour, 2004).
Aberdeen Group found (2012) that leading companies are 50% more likely than their
peers to credit success to effective systems engineering. Gains recorded include:
Met 88% of quality targets
Met 86% of revenue targets
Met 85% of product launch targets
12% decrease in development time over previous years
9% increase in profit margins on new products.
A model-based approach to product line engineering delivers 23% more projects on
time, at 62% lower cost, than alternatives – based on a survey of 667 engineering
respondents conducted by analyst firm Embedded Market Forecasters (J. Krasner,
2014).
Definitions
Term Definition Source
Intellectual Something (such as an idea, Merriam-Webster
Property invention, or process) that dictionary
comes from a person's mind
Model-Based MBSE is the formalized INCOSE MBSE
Systems application of modeling to Initiative
Engineering - support system requirements,
MBSE design, analysis, verification
and validation, beginning in
the conceptual design phase
and continuing throughout
development and later life
cycle phases
Product Lifecycle A strategic business approach CIMdata – “PLM
Management that applies a consistent set of – Empowering
(PLM) business solutions in support the Future of
of the collaborative creation, Business” report
management, dissemination,
and use of product definition
information across the
extended enterprise from
concept to end of
life—integrating people,
processes, business systems,
and information
Systems SE is an interdisciplinary INCOSE Systems
Engineering approach and means to enable Engineering
the realization of successful Handbook v.
systems 3.2.2, page 6
References
Aberdeen Group 2012. “The Strategic Role of Systems Engineering: Ensure the Future
Success of Your Products” Aberdeen Group Report
CIMData 2010. “Product Lifecycle Management – Empowering the Future of Business”
CIMdata Report
Friedenthal, Sanford et al. 2007. “INCOSE Model Based Systems Engineering (MBSE)
Initiative” INCOSE 2007 (San Diego, CA, US).
Garro, Alfredo and Tundis, Andrea 2012. “A Model-Based Method for System Reliability
Analysis” SpringSim 2012 (Orlando, FL, US)
L. Rogovchenko-Buffoni, P. Fritzson, A.Garro, A. Tundis, and M. Nyberg, Requirement
Verification and Dependency Tracing During Simulation in Modelica, Proceedings of
the 8th EUROSIM Congress on Modelling and Simulation (EUROSIM 2013), Cardiff,
Wales, UK, 10-13 September, 2013.
Honour, Eric 2004. “Understanding the Value of Systems Engineering” INCOSE SECOE
Krashner, Jerry 2014. “How Development Organizations can Achieve Long-Term Cost
Savings Using Product Line Engineering (PLE)” Embedded Market Forecasters Report
Porter, Michael and Heppelmann, Jim 2014. “How Smart, Connected Products are
Transforming Competition” Harvard Business Review, Nov. 2014
PTC eBook, 2012. “Forces of Transformation” (Available at
http://www.ptc.com/about/manufacturing-transformation)
SE Handbook Working Group 2011, “SYSTEMS ENGINEERING HANDBOOK” v3.2.2,
INCOSE
Singer, David et al. 2009. “What is Set-Based Design?” ASNE DAY 2009, National Harbor,
MD.