-The industrial product development is currently managed by resorting to the Model Based Systems Engineering (MBSE), aimed to decompose the systems complexity, to the Lean Manufacturing, allowing to achieve the targets of Quality, Cost and Delivery (QCD), and to the enabling technologies of the Smart Manufacturing. Those three approaches are still assumed completely uncoupled, against the evidence of the disruptive power of their mutual and full integration, as is herein discussed. This integration looks the goal to be achieved for a definitive assessment of the so-called strategic initiative “Industry 4.0”, as is currently promoted worldwide to improve the industrial productivity.
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INTRODUCTION
The most recent transformation of the worldwide
industrial organization aims to improve the system quality, to
reduce cost, and to finalize the product delivery to the
customer needs [
(SM) is herein proposed, by analysing methods, processes, tools applied by each approach. As a result, they look like the edges of an ideal triangle, which defines the perfection of their full integration for a unified approach to design, to produce and to deliver.
II.
CHARACTERIZING THE MBSE, LM AND SM
To synthetize herein briefly, the MBSE primarily looks at
the product as a complex system and helps the designer and
the manufacturer to manage the whole Product Lifecycle
Development. The MBSE allows decomposing the system
complexity, and assuring a complete traceability of the
system requirements to functions, of functions to subsystems
and components, of subsystems to the built parts, classified
by a part number. This action is effectively performed, by
resorting to some pillars, like the method, the process, the
tools and the data management [
The methodology includes a preliminary selection of a
suitable model of the Product Life Cycle, as the well-known
“V–diagram” depicted in Fig.1, and even other ones [
This model clearly states the relevant role of the customer in defining the system requirements and the importance of the stakeholders. The design activity (Application Lifecycle Management, ALM) is somehow mirrored, by level, with the corresponding actions of manufacturing (Product Lifecycle Management, PLM), and links the system conception to its production, through the “V” look of the diagram. A key issue of this method is that it applies some reusable and digital models. They include a qualitative description of the system behaviour, architecture and operation (functional modelling) and a quantitative one (physical or better numerical modelling), based on a numerical and mathematical structure. The numerical modelling is exploited to describe the system geometry, to predict its performance, to make a trade-off of its configurations, typically by resorting to an heterogeneous simulation, in which the functional and the physical models are both included. The verification of requirements and the product validation even resort to those models to check the correspondence between product and model, and between product and customer needs, respectively.
The process brings the user to perform the requirement analysis, then the operational, functional, logical and physical analyses, in sequence, to reach a design synthesis. The tools exploited include some typical diagrams, defined within a standard language, as the SysML, but even some architecture frameworks, as they are defined, for instance, by several Departments of Defence (DODAF, MODAF, NAF) or some Space Agency (ESAAF). Particularly, some typical system capabilities, which are exploited in operation, are identified within the architecture framework, through several views of the system, and this helps the designer to define the best solution among those proposed.
Finally, several tool software are interoperated through a
platform, which defines a tool chain, including several data
bases, which need an effective data management to share the
information, through a careful control of changes introduced
by the operators, classified by a hierarchic level. It is worth
noticing that nowadays aside a functional analysis a
dysfunctional is already accomplished in the preliminary
technology trade–off [
The MBSE offers some typical features to help the
product developer in reaching the goals above mentioned. As
Fig.2 shows, the two common activities of the trade-off
analysis and of the requirements verification and system
validation (V&V) are deployed by resorting to the three
typical analyses of requirements, functions (and operations)
or dysfunctions, and physics of the system. More recently,
the application to the industrial product and no longer only to
the software, suggested of decomposing the functional
analysis into a preliminary identification of functions and
operations and then of the logical activities performed by the
system architecture, thus adding the logical analysis as an
intermediate step of the design activity [
It is worth noticing that nowadays the MBSE approach
includes a combined functional and non-functional or
dysfunctional analysis to anticipate the prediction of system
reliability, since the preliminary design activity [
COMMON ACTIVITIES
TRADE-OFF: Define alternative solutions and optimise NUMERICAL MODELING
INTEROPERATED
MODELS HETEROGENEOUS SIMULATIONS
V&V: VIRTUAL AND REAL
TESTING
CONTENTS, TOOLS AND PRODUCTS Customer needs and Mission, Scenarios business modeled Contexts Requirements Requirement diagram
FuDnyctsifounnsctainodn/sor bdAlicaotgcivkrai,tmyP,asSc(ekBqaeguheean(vAcieorc,uhSri)tt;aeBtcelto,uUcrkes,)eInctaesrenal FUNCTIONAL Functional architecture FUNCTIONAL BREAKDOWN STRUCTURE ANALYSIS
(FBS)
ANALYSES REQUIREMENTS ANALYSIS Product integration and design synthesis HOMOLOGATION / LIABILITY
RAMS
TARGETS
The analogy between functional and dysfunctional behaviors is defined. As the functional analysis focuses on the functions, the functional hazard analysis identifies the system failures. Similarly, a logical component performs a logical operation, while in the other analysis it is required to assure a target of reliability, which becomes a real reliability performance in the final product, as a commercial component is identified to physically provide that logical operation.
When the MBSE approach is implemented, a digital
model of the whole product is preliminarily synthesized and
used to predict the product performance in operation.
Particularly, the FBS, as is depicted in Fig.4, representing
the example of a flywheel on magnetic suspension, is used
to generate an IBD, for instance, which allows the trade-off
analysis [
The software tools used to build up the digital model
need to be interoperated, i.e. connections must allow a
straight transition of information between the tools [
Many approaches currently applied to the process management, more than to the product development, as the SE does, including the Total Quality Control (TQC), or
basically resort to the Japanese philosophy of the Gemba
Kaizen [
The three pillars of the LM are the so–called housekeeping (HK), the identification and elimination of inefficiencies or muda (ME), and the assessment of suitable standards to be repeatedly applied, by the operator, to the process (STD).
As for the SE, a method can be identified in the practice of Gemba Kaizen. The process management is meant to perform simultaneously two actions, as the maintenance of the existing practices and their continuous improvement. The first rule applied is “Plan–Do–Check–Act” (PDCA), then a coherent standardization follows, and applies the rule
those activities concern the priority of quality over all; the use of data, collected and retrieved by the process, to evaluate its effectiveness, but even to create a base for a statistical analysis; the target of customer needs and satisfaction as a unique and real target of the whole process.
Several tools are exploited. A policy is first stated, to define the object of improvement (policy deployment), then people are involved through the Quality Circles, being groups of operators asked to express their useful suggestions about any process inefficiency (QC). Particularly, they must monitor the effectiveness of operations, to reduce the fatigue of operators, by increasing the ergonomics, safety, productivity, quality, and security, and decreasing the production time and cost.
The operators express their suggestions, through different means, but all concern the quality improvement, the cost reduction and the delivery enhancement (QCD). Upon the suggestions received, the management defines some standards, and then the operators, who drive their continuous refinement, test them and allow a definitive assessment.
When the Gemba Kaizen is applied, several paths are followed, constituting a sort of checklist of activities. They are organized like into a matrix form. The rows of that ideal matrix are the three activities of HK, ME, and STD previously described. They define the items of the process management, somehow like the use cases of the SE. The matrix columns are the three main goals defined by the QCD system. They define also the metrics to be applied, to evaluate the effectiveness of the running process. Particularly, when the manufacturer plains the activity, he defines the Quality Function Deployment (QFD, related to ISO 9000 series and 14000 and others), the Cost metrics (about product quality, productivity, stocks, production line flexibility, machinery stops, use of space, lead-time), and Delivery targets (efficiency, promptness, completeness, time, related to the implementation of the JIT).
The maintenance is performed by implementing the housekeeping, and five activities are performed. They compose the so–called set of “5 S” (seizi = clean out the production line; seiton = configure properly what you kept in line; seiso = clean the machinery and check; seiketsu = applied the three above steps to the operators; shitsuke = assure the self-discipline of the operators, write the standards and make some practices). According to that scheme, the rules of housekeeping are defined, and the related standards are written.
The standardization is even deployed by considering the targets of quality, by resorting to a list of five issues, known as the “5 M” items (men, machinery, materials, methods, metrics).
The improvement is based on the elimination of inefficiencies or muda, and is performed by identifying the root cause by answering to a sequence of the so–called five “why?” or “5 W”. A classification of muda into mura (changes, variations, irregularities) and muri (excesses), respectively, helps in sorting the problems to be solved. They consider seven typical categories (7 muda), as the excess of production, the excess of stocks, inefficiencies related to product defects, operator motion, process performance, late incoming of goods in production, and transportation systems.
The architecture of the Gemba is even well defined. The
Gemba House, like in a framework, describes it completely
[
CELL A
PROCESS 1 SEPARATOR
MATERIAL DISTRIBUTION
PROCESS 1 SEPARATOR
CELL B
PROCESS 1 SEPARATOR
MATERIAL DISTRIBUTION
PROCESS 1 SEPARATOR PROCESS 2
PROCESS 2 WASTE
SEPARATOR
DELIVERY WASTE
SEPARATOR
DELIVERY
The Gemba includes also a hierarchy of managers and
operators, all playing a specific and delimited role (to be
interpreted as cells of people). The model of Learning
Enterprise, where everybody sees, observes and suggests, is
implemented, through an operational chain starting from the
CEO (Chief Executive Officer) and going to the workshop
operator, through the chiefs of unit, department, and section.
Therefore, the LM exploits a real Training Within Industry
(TWI) [
The performance of process is easily evaluated, by filling, along the production line, the so–called Value Stream Map (VSM), in several data boxes, where all the indexes describing the effectiveness of the running process are certified.
Proposing in few sentences a complete description of the
strategic initiative “Industry 4.0”, resorting to the Smart
Manufacturing aimed to enhance the industrial productivity,
is rather difficult. Nevertheless, it is known that the Fourth
Industrial revolution [
They support the creation of suitable infra- and intrastructures to implement the SE and the LM. Smart and intelligent systems are widely interconnected, to perform a true collaborative and somehow autonomous work, to be adaptable to the working environment changes, to allow a continuous and effective monitoring, prognosis, diagnosis and control of systems in operation.
To investigate the interaction between SM, MBSE and
LM, a short synthesis of the enabling technologies
characterizing the fourth revolution is proposed in Fig.6,
according to [
2
Advanced Manufacturing Solutions (Collaborative Robotics)
Additive Manufacturing
Augmented reality
Horizontal and Vertical Integration (Units, Sections, Departments) 3 7
Cloud 8
Cyber-security
Big Data and analytics 1 9
One of the main goals of those technologies is allowing a cyclic use of products, i.e. monitoring and maintenance of the manufactured systems should increase the possibility of re-use or longer use. A crucial issue is the integration of manufacturing units spread on the different locations (horizontal), with customers and suppliers, as well as that between the design, the management and the workshop, inside the same factory (vertical).
All the enabling technologies introduced support an
effective enhancement of the manufacturing performance,
quality and safety, because they are based on the extensive
use of both the mechatronics and the digitalized information.
The system smartness is often related to different levels of
artificial intelligence, corresponding to some functions of
sensing, controlling and actuating, under a defined strategy
[
The collaborative robotics helps humans in making
faster, controlled and more precise the manufacturing action,
improving the performance, decreasing the pain of operators
and assuring high levels of quality and safety. The design of
collaborative robotic devices surely faces some issues related
to complexity and to the actual needs to be satisfied, as in the
exoskeletons. The intensive use of automation in
manufacturing and material processes increases the
complexity related to multi-physics involved in the coupled
phenomena exploited [
The additive manufacturing introduces another kind of smartness, related to the digital content of information directly sent by the designer to the production line, extensively adaptable to many needs of shaping and optimizing the product. It allows manufacturing systems and components previously never built up, because of some surface inaccessible to the tooling machines. The strength of additive manufacturing is the lying of production data directly within the digital product mock-up, made through the SE as a result of the trade-off accomplished between technologies.
Two examples might simplify the above mentioned
concepts. The so-called smart bearing, for instance, is
embedded into the machinery as a component of the whole
assembly, but is even equipped with some miniaturized
sensors, which allow monitoring the inner environment of
bearing, to prevent failures and damage, but even the outer
and surrounding environment of the hosting frame, as it
measures the loading, thermal, vibration and acoustic
conditions [
Rolling mill vibration monitoring
Roller bearings
Sensors
Data acquisition
Wireless connection Data elaboration Vibration and kinematic energy harvesting via piezoelectric / magnetic coupling
Diagnosis / Prognosis / Control / Maintenance
It might be used as a sentry node of a network to warn the
operators about any abnormal behavior of either the bearing
components or the hosting system. If it is used remotely, it
allows applying the IoT technology, to monitor the life of
components and warn the manufacturer about any need of
maintenance. In case of the active magnetic bearing, the
system simultaneously performs the monitoring action and
the active vibration control. To install the smart bearing it is
required a deep description of its calibration and properties,
which is digitally provided, since its production, through the
ISO Data Matrix method [
The augmented reality is another effective mean to
implement the smart manufacturing, as in case of the smart
helmet for operators involved in steelmaking or similar
industrial plants. Basically, this tool provides two services.
The information coming from some sensors embedded and
from the network are plotted through a head-up display, and
read in real time by the user. These data might prevent the
exposure of the worker to some risk or any severe operating
condition. Some recent evolutions of this device include a
smart glass, allowing to look at the working environment
through a glass shield, whose transparency and color can be
regulated by resorting to either thermochromic or
electrochromic material [
All those systems exploit a variety of coupled phenomena and include a number of components that their complexity easily rises up and requires some systematic approach to design the device, as the MBSE, and to perform the detection of waste, according to the LM approach. PROCESS management Visual management Continuous improvement Apply the Learning Enterprise approach Improve quality Reduce cost Avoid human mistakes in processing Improve delivery process Flexible production line (Gemba) Self-disciplinated operators Reliable machinery Data retrieving Customer Stakeholders Operators Gemba (Process cycle) Model of process: Total Flow Management Process maintenance Process improvement Housekeeping Elimination of Muda Standardization
Quality Cost
Delivery Identification and charcterization of Gemba Housekeeping: apply "5S" Planning of process … ...(Plan-Do-Check-Act PDCA) Standardization: apply "5M" Standardization of process… ... (Standardize-Do-Check-Act SDCA) Elimination of inefficiencies: apply "5 W" (Muda identification) Classification of muda - mura - muri… ...and problem solving Driving lists 5S (Housekeeping); 5M (Quality and standards);… ...5W (Root cause); 7 Muda VSM - Value Stream Map (of Data) Diagrams Example: Fish Diagram Procedural frameworks TQC - TQM - JIT - TPM - QFD The Gemba House Standards Value Stream Map Key Performance Indicators (KPI) Process driveline Operator hierarchic chain Data bases Operators team Quality Circles (QC) who express visual suggestions 5 6 7 8 9
Horizontal / Vertical Integration Industrial Internet Cloud - IoT Cyber-security Big Data and Analytics 1
TOWARDS A UNIFIED APPROACH
If one compares the two approaches of the MBSE and the
LM actually realizes that a punctual correspondence exists.
That comparison is tentatively proposed in Fig.9.
Particularly, following some typical references as
[
As is evidenced by Fig.9, the MBSE applies to the industrial product a methodology that is similarly applied to the process by the LM. An almost perfect dualism is perceived. In some cases a superposition of contents occurs. For instance, the goals are the same, they focus on quality, cost, mistake, and inefficiencies. In the LM the role of humans is very evident and the operators are elements of the process, like in the MBSE, although they are less expressively evidenced. The actors are even the same, and customer plays a crucial role. The data are extremely important in both the drivelines B.
Analysing deeply the synopsis, one can find some dualisms and analogies. A first evident dualism involves the requirements of the product development and the standards of process deployment. They are both used as a reference for the verification and validation, they come out from an iterative process of assessment and refinement, which motivate resorting to all of tools foreseen in the two contexts. The requirement traceability is a key issue of the SE methodology, as in the LM the Visual Management is, i.e. for a continuous improvement the information, the problems and the corrective actions applied must be clearly accessible by all of the operators. For both the digitalization is a crucial target of innovation, as is promoted by the SM, but even the effective integration among units (horizontal and vertical).
In both the contexts, decomposing the complexity is a priority, in the MBSE simplifying the system architecture is mandatory as well as making lean the process is the goal of the LM. The goals even include a difference like the reduction of cases of re-engineering in the product design, and the improvement of delivery, in the process design. They are both focused on the overall process implemented and they promote a unique execution, to keep the costs as low as possible. The implementation of the two methodologies of the MBSE and of Gemba Kaizen look needing a straight use of augmented reality, simulation and modelling, as well as an efficient communication and sharing of information, through the internet.
The needs express a complementarity of exigencies, i.e. the MBSE expressively requires suitable tools for modelling, interoperated and reliable, based on secure data; the LM points out the need for machinery and operators, reliable and very well interfaced, by some suitable Man to Machine systems (M2M), and more in general by Human Machine Interfaces (HMI). Actually, both the drivelines exploit all of those elements. Moreover, the attention to stakeholders is high in both the contexts.
As the method is implemented, it can be realized that despite the difference of nomenclature and of the context (product vs process) a certain dualism is present. The ALM activity is mirrored in the “V-diagram” by the PLM, as in the LM maintenance is alternately performed with improvement. The targets are analogous; since the aim of product development is the RAMS as in the process, the quality must be assured. The sustainability pursued in the product development corresponds to the efficiency in process, and both require keeping cost low. The output of MBSE is the service as a phase of the delivery, being the target of the LM.
The different steps of process, in both the contexts, express a dualism. In the product development, the analyses are performed in sequence, and in the manufacturing, actions are executed in sequence, by resorting to a number of conventional driving lists (“5 S”, “5 M”, “5 W”, 7 muda), as well as in the MBSE, the applied language provides several suitable diagrams. Even in the LM, some diagrams are plotted and exposed in the production line, to involve the operators in the continuous improvement, as the Ishikawa diagram or “Fish” Diagram, where the targets of QCD are related to the 5M at different levels, and to the environment. The smallest arms in this diagram are the so–called key points for the punctual intervention of change (Fig.10). For all those activities, the use of tools to implement a heterogeneous simulation is mandatory, as well as the support of an effective cloud and of the internet, to allow a complete interoperability. The data sharing and management is crucial, thus requiring a perfect horizontal and vertical integration, and to resort to some software deploying the
Men
Machinery
Materials
Issues
Goals
QCD Key point Environment
Methods
Metrics
Deployment Fig. 10. The Ishikawa or “Fish” Diagram, used in the Lean Manufacturing.
It is worth noticing that in both the contexts, the frameworks play a significant role. The MBSE resorts to the architecture frameworks to deploy the system, in terms of capabilities and views, as the LM actually implements several procedural frameworks (the Gemba House or the TQC, JIT, QFD) to manage process, materials and time.
By converse, it is relevant that the MBSE totally trusts in the language used to create the digital models, while the LM directly organizes the operators, both in hierarchy and in groups, or Quality Circles, to retrieve the information and to support the improvement. Similarly, if one looks at the platform applied, the tool chain is dominant in the MBSE while the LM focuses on the operator chain. two
Concerning the information, a superposition between the approaches occurs. The elicitation of traceable requirements, linked to the customer needs, corresponds to the assessment of the process standards, based on customer needs (where customer might be even the following manufacturing unit), but refined step by step through the concurrent contribution of all the operators or the stakeholders. The Value Stream Map is somehow overlapped to the quantitative contents of data shared in the product development.
definitely recommended by both the SE and the LM approaches. They define the metrics used to evaluate the product and the process, respectively, and provide a list of suitable items about which the analysis can be effectively performed. In the LM some KPI are frequently used as the
At higher level, it might be noticed that as in the SE the
organization driving the building up of a tool chain to control the changes, in the Gemba Kaizen, the Total Flow Management drives the strategy of production. It might be oriented to a “one piece flow”, with a synchronization based on the “Just in Time”, to perform a “pull production” more than to a “push production”, since it is excited by the customer demand.
The impact on those analogies of the SM looks large, according to the feedbacks collected. If one looks at the proposed association between the enabling technologies and the items identified for both the methodologies (Fig.9), immediately can realize that a good coverage is assured.
Moreover, the contribution of advanced mechatronics, in terms of advanced solutions for manufacturing and robotics and augmented reality is relevant and affects both the product development and the process deployment. By converse, the Additive Manufacturing, nowadays so strategic, provides a good contribution in some issues, while the perception of a huge impact on the overall system looks lower.
The simulation still represents an important element, particularly in the meaning of extended heterogeneous simulation, including functional and numerical modelling.
than an input for the application of such unified approach, although a preliminary organization of the working units and of the operators to be effectively integrated is needed, to apply the disruptive technologies above described.
All the issues related to the network, the data collection, elaboration, transmission and management are crucial, for many activities here mentioned. Particularly, the technology and the infrastructures related to the industrial internet and to the cloud is perceived as a key element of powerfulness of the whole rationale. The impact of the Big Data and analytics is impressive, although the cybersecurity might be, simultaneously, the element either of strength or of weakness of this system.
As it was demonstrated, a relevant issue of the convergence among MBSE, LM and SM is the customization of product. More and more the customers require a personalized version of product, or better a complete satisfaction of needs. This can be assured, thanks to flexible and lean production lines, as well as by means of smart systems and equipment, easily adaptable. The smartness often increases the system complexity, thus motivating the application of the MBSE to decompose and handle it.
What kind of benefits a final integration of the MBSE, LM and SM might provide? To this question, some answers are proposed.
and complete the assessment of the Product lifecycle model
assumed by the SE. Particularly, it is well known that a link
between the ALM and the PLM or PDM (Product
Deployment Management) is established by the SE tools, and
is currently exploited to clearly define the requirements
related to manufacturing. Nevertheless, the SE very seldom
defines in details the activities foreseen by the ascending arm
of the “V-diagram”, visible on the right, in Fig.1. A clear
decomposition of the actions after sale, as the delivery, the
service, the maintenance are seldom defined, as in some
specialized contribution as in [
B. The Gemba looks like a system and, in principle, no
limitation inhibits to apply some of the tools of the SE to the
process, once that the production line is identified as the
system to be analysed. Particularly, the diagrams exploited
by the SysML to decompose the system complexity might be
freely used to analyse the process. Some specialized
diagrams, as the State Machine, can be even simulated to
check the performance of the system [
C. The integration between LM and SM looks natural, if
one assumes that the SM is conceived to enhance the
productivity. Many enabling technologies are required to
make faster, more effective and more precise the action of
improvement. Nevertheless, all the technologies supporting
the monitoring, prognosis and diagnosis activities will
provide a key contribution. Particularly, if the remote control
currently applied to systems in operation, like motor
vehicles, trains, aircrafts and spacecrafts, will be even
applied to the elements of manufacturing systems, for
instance to the bearings, to retrieve data for an effective
maintenance [
It is known that mechanical components requiring a continuous maintenance, being designed for a finite life and somehow consumable, need a clear traceability of their intrinsic and operational data since the testing performed before the delivery. Therefore, a real horizontal integration with customer will be complete, when the test, the service and the maintenance will be suitably monitored and coupled. This action resorts to the SM smart systems and data management ass a key element of the infrastructure to actuate the remote testing and operation monitoring.
two levels. If one looks at some smart systems like robots, mechatronic and autonomous systems, the system integration is suitably driven by the MBSE, through all its tools. Nevertheless, if the activity of remote monitoring is designed, the MBSE is helpful to define all the system parameters, considering the mission, operation and requirements, related to service. Quite often, it happens that despite the application of remote monitoring systems connected through the cloud, the designer is poorly aware about the real specifications required by the application, since a too short investigation about the requirements and the functions to be exploited is preliminarily performed.
E. To clarify the mutual integration of the MBSE, LM,
and SM, the example of the smart bearing looks suitable. It
is first a product to be developed and equipped with a set of
sensors, then it becomes a node of the monitoring network
and can perform the in-monitoring of its own defects and
failures, as well as the out-monitoring, i.e. it is a sentry of the
process performance for the machinery, where is embedded.
Moreover, the bearing as a system to be tested needs a test
bench for a complete homologation. The results of this
activity are enclosed into the firm of the bearing, nowadays
traced, by the labels applied, easily detected and read in
operation, according to the ISO Data Matrix [
This example clarifies the mutual interaction occurring between the MBSE, the LM, and the SM. Actually, when the product bearing is developed, the required testing and monitoring activities are designed together the system, through the PLM, within the MBSE approach. In service, it plays the role of system exploited to support the process, as a mechanical component, but even to monitor its performance, as a node of the IoT, thus contributing to the data retrieving useful to implement the LM. As a smart system, it resorts to the disruptive technologies of the SM, including the mechatronics, the IT, especially in terms of cloud, network, data management and storage.
IV.
CONCLUSION
A full integration among the MBSE, the LM, and the SM is the natural path for the final assessment of the “Industry of the Future” strategy. They certainly help in assessing the required standards, to assure the security and safety levels in products and processes, compatible with the desired sustainability.
The means to perform that integration are currently available, or at least are in rapid development. Despite the different origins, all those levers for innovation focus on the same goals. They are motivated by the need of satisfying the customer, by assuring quality, keeping cost as low as possible, improving service and delivery. To assure a complete integration, some actions are required.
A full awareness of people about the powerful contribution of the MBSE-LM-SM system must be reached. This activity is currently promoted by the educational programmes to the digital factory, worldwide proposed, and especially by some dedicated competence centres.
To refine the tools of that synoptic system, the disciplines
of mechatronics [
For the product development, the main stream of
innovation concerns the application of the digital twin and
functional modelling in addition to numerical modelling, for
a comprehensive virtual engineering, prototyping and testing
[
Other technologies are strictly involved, as the ICT, with particular care of the network band and configuration, as the 5G. In addition, even the HMI systems could improve the impact of the proposed approach. A crucial issue concerns the inclusion into the global deployment environment previously described of optimized business models, supply chains, logistics to configure a balanced ecosystem in the factory.