Systemic Intelligence provides industry-leading services to support every step
of your Systemic Digital Twin journey
Systemic Intelligence provides end-to-end support that covers the development and integration of Systemic Digital Twins, adapted to your needs and sector specificities
A pragmatic approach
In order to help our customers starting their systemic digital twin journey, we consider two main phases for a given industrial system:
➤ a business study phase, where we shall define a system model of the considered industrial system, develop a minimum viable product (MVP) for an associated systemic digital twin and manage the first business analyses on this basis in order to prove the value of the approach.
➤ a scale-up & integration phase can then be managed to construct an operational systemic digital twin, fully integrated within an industrial information system. We can then also provide adapted supporting business & technical services such as WorldLab™ and Σ™ training, technical expertise, etc.
This initial phase consists of understanding the business issues at stake through a relevant modeling of the system of interest, developing a WorldLab™-based proof-of-concept of a corresponding systemic digital twin that supports the initial business problem resolution, and finally managing a business study which solves the initial issues, based on the developed systemic digital twin.
Understanding the problem(s) to be solved and modeling the system of interest
To move towards a systemic digital twin for an industrial system, the very first step is to fully understand the problem(s) to be solved, that motivate the construction of a given systemic digital twin, by answering to the following questions:
– what are the business objectives to be achieved for the industrial system?
– what are the strategic decisions that one wants to make and in which context?
– what is the exact / specific business & technical scope which is concerned?
– what internal & external data should be analyzed & used?
This initial work represents 60 % of the global effort required to construct a systemic digital twin. It requires strong interactions with the customer teams in order to guarantee the relevance of our work with respect to the business reality to capture and the actual business objectives to achieve. The key activities are here:
➤ Identifying the specific operational use cases – with associated KPIs – to be addressed
➤ Formalizing the business & technical scope by a suitable environment diagram
➤ Defining the functional interactions involved on the selected scope
➤ Consolidating a medium-grain system model of the industrial system of interest
Developing a first systemic digital twin
The second step of the construction of a systemic digital twin consists in the technical development of the systemic digital twin with WorldLab™. We shall use at this stage an agile & interactive process which deals with the following key activities:
➤ Analyzing the business data to feed the systemic digital twin
➤ Identifying the business scenarios to simulate with their parameters
➤ Constructing a Σ™ model based on the system model provided by the first step
➤ Designing the end-user graphic interface of the systemic digital twin that reflects the business objectives & decisions to support
➤ Developing an initial version of the systemic digital twin of the system of interest
➤ Verifying that historic data can be recovered with the systemic digital twin
➤ Capturing the first feedbacks on this initial version & consolidating a final version integrating these feedbacks
Using the systemic digital twin to support a business study
The third and last step of the construction of a systemic digital twin consists in using it to support a WorldLab™-based business study focused on the resolution of the initial business issues, which also allows to validate the systemic digital twin. In this matter, key activities are:
➤ Simulating the chosen business scenarios and computing the associated key performance indicators
➤ Analyzing the results of the simulations from a business perspective
➤ Capturing your feedbacks on the simulation results
➤ Managing the evolutions of the systemic digital twin based on your feedbacks
Scale Up & Integration
This second phase involves extending an initial proof-of-concept of a systemic digital twin through scale-up and business & IT integration to deliver a full-fledged operational systemic digital twin, fully aligned with your business needs.
The Scale-Up & Integration service especially conssts in enhancing & robustifying, when necessary, the systemic digital twin obtained during the initial business study phase in order to align it with the complete specific business needs & scopes of our customers and managing moreover the following specific challenges:
➤ Data integration in order to connect the systemic digital twin with operational data, either internal to a given company or coming from public external sources,
➤ Business integration by identifying the various actors who will use & operate the systemic digital twin and defining the corresponding scopes of use for each business actor.
➤ Training the various actors who will be responsible for operating the systemic digital twin, according to their scope of use.
We won’t let you down: Systemic Intelligence provides training and assistance for those developing and using systemic digital twins.
How to develop a systemic digital twin?
0 – Introduction to systemic digital twins
1 – The initiation phase: understanding the relevant scope of interest
1.1 – Eliciting the business strategy
1.2 – Modeling the industrial system of interest
1.3 – Identifying the data to consider
1.4 – Application exercise on the initiation phase
2 – The specification phase: specifying finely a systemic digital twin
2.1 – Architecting the simulation model
2.2 – Analyzing the business data
2.3 – Specifying the systemic digital twin
2.4 – Application exercise on the specification phase
3 – The development phase: developing a systemic digital twin with WorldLab™ and Σ™
3.1 – Developing the core Σ™ model of the systemic digital twin
3.2 – Designing the user interface of the systemic digital twin
3.3 – Verifying & validating the systemic digital twin
3.4 – Application exercise on the development phase
4 – The use phase: using WorldLab™ to analyze the business use cases
4.1 – Identifying the business scenarios of each use case
4.2 – Evaluating & comparing the business scenarios of each use case
4.3 – Application exercise on the use phase
How to become a Σ™ expert?
1 – Introduction
2 – Getting started
2.1 – Σ™ ontology
2.2 – Systems and variables
2.3 – Redeclarations
2.4 – Activities
2.5 – Executions
2.6 – Terminology and additional syntactic constructs
2.7 – Application exercise
3 – Variables
3.1 – Basic types and domains.
3.2 – State and temporary variables
3.3 – Constants and parameters.
3.4 – Observers
3.5 – Indicators
3.7 – Application exercise
4 – Expressions
4.2 – Constants
4.3 – References to variables and parameters
4.4 – Boolean expressions
4.5 – Inequalities
4.6 – Arithmetic expressions
4.7 – Built-in functions
4.8 – Conditional expressions
4.9 – Probability distributions and random deviates
4.10 – Time primitives
4.11 – Application exercise
5 – Instructions
5.1 – Skip
5.2 – Assignment
5.3 – If-Then-Else
5.4 – While
5.5 – Return
5.6 – Blocks of instructions
6 – S2ML constructs
6.1 – Cloning
6.2 – Classes and instances
6.3 – Polymorphism and inheritance
6.4 – Attribute (re)declaration
6.5 – Splitting the model into several files
6.6 – Synthesis exercice
Process & system analysis is far from trivial, especially when it is done in order to support the authoring of system models for simulation. Fortunately, Systemic Intelligence provides a world-class expertise in industrial processes modeling.
While WorldLab™ and Σ™ were designed in order to be as-easy-as-possible to use, technical problems may occur in practice. In this matter, our technical teams are ready to answer to any of your questions regarding the use of our systemic digital twin platform.
Do not hesitate to contact us in both cases.