Puneet Patwari

The use of System Engineering (SE) language such as SysML [1,20] is common within the community of control system designers. However the design handoff to the subsequent phases of the control system development is carried out manually in most cases without much tool support. This results in non-uniformity in the overall system design since individual groups invent their own vocabulary while using a language like SysML which leads to inconsistencies across the design, interface and realized… Show more

The use of System Engineering (SE) language such as SysML [1,20] is common within the community of control system designers. However the design handoff to the subsequent phases of the control system development is carried out manually in most cases without much tool support. This results in non-uniformity in the overall system design since individual groups invent their own vocabulary while using a language like SysML which leads to inconsistencies across the design, interface and realized code. To mitigate this, we propose the development of a Monitoring and Control Modeling Language (M&CML), a domain specific language (DSL) [4,22] for specifying M&C solutions. Show less

In system engineering, it is a common practice to start exploring the solution space through usage of design mechanisms such as SysML, a modeling language for expressing system design. The usage of such methodologies allow creating design of target solutions through identification of use cases, components, their interfaces, interaction data models and so on. Since it is a generic language, the concepts in SysML require manual mapping to the concepts in the problem domain so that the target… Show more

In system engineering, it is a common practice to start exploring the solution space through usage of design mechanisms such as SysML, a modeling language for expressing system design. The usage of such methodologies allow creating design of target solutions through identification of use cases, components, their interfaces, interaction data models and so on. Since it is a generic language, the concepts in SysML require manual mapping to the concepts in the problem domain so that the target design could be expressed in domain terms. To solve the process of creating design solutions specific to a domain, we propose an approach which includes defining a design environment that is domain aware. It has been referred to as a Domain Specific Engineering Environment (DSEE). Show less

Model Driven Engineering (MDE) as a key driver to reduce development cost of M&C systems is beginning to find acceptance across scientific instruments such as Radio Telescopes and Nuclear Reactors. The creation and maintenance of models is still a significant challenge to realizing MDE benefits. However, large projects involve several such domains, and there is still a need to interconnect the domain models, in order to ensure modelling completeness. This paper presents a knowledge-centric… Show more

Model Driven Engineering (MDE) as a key driver to reduce development cost of M&C systems is beginning to find acceptance across scientific instruments such as Radio Telescopes and Nuclear Reactors. The creation and maintenance of models is still a significant challenge to realizing MDE benefits. However, large projects involve several such domains, and there is still a need to interconnect the domain models, in order to ensure modelling completeness. This paper presents a knowledge-centric approach to doing that, by creating a generic system model that underlies the individual domain knowledge models. Show less

Large projects such as Square Kilometer Array comprise of distributed teams developing parts of the control system. To exchange design thinking early in the development life cycle, teams use SysML based tools to capture design in a structured form. Since SysML is unaware of the application domain it is unable to reason about these designs created across teams. Based on our experience with such projects, we created a domain intelligent environment that significantly enhances the support towards… Show more

Large projects such as Square Kilometer Array comprise of distributed teams developing parts of the control system. To exchange design thinking early in the development life cycle, teams use SysML based tools to capture design in a structured form. Since SysML is unaware of the application domain it is unable to reason about these designs created across teams. Based on our experience with such projects, we created a domain intelligent environment that significantly enhances the support towards the design Show less

When we design and develop a system, knowledge about the problem and solution is typically fragmented across a number of tools and models – and the minds of the engineering team. Unified system modelling tools capture the overall problem and solution at a certain level of abstraction, but detailed knowledge and decisions remain scattered across multiple environments. We are exploring the possibility of creating SystemMaps, a unified repository for system knowledge that can serve as an… Show more

When we design and develop a system, knowledge about the problem and solution is typically fragmented across a number of tools and models – and the minds of the engineering team. Unified system modelling tools capture the overall problem and solution at a certain level of abstraction, but detailed knowledge and decisions remain scattered across multiple environments. We are exploring the possibility of creating SystemMaps, a unified repository for system knowledge that can serve as an underlying integrating layer across the various tools and models. Our goal is to explicate and capture the semantics of the relationships among the various models, to enable consistency checking among them. Show less

Development of similar systems leads to a strong motivation for reuse. Our involvement with three large experimental physics facilities led us to appreciate this better in the context of development of their respective monitoring and control (M&C) software. We realized that the approach to allowing reuse follows the onion skin model that is, building reusability in each layer in the solution to the problem.

Abstract Control systems for radio astronomy projects such as MeerKAT [1] require testing
functionality of different parts of the Telescope even when the system is not fully developed.
Usage of software simulators in such scenarios is customary. Projects build simulators for
subsystems such as dishes, beam-formers and so on to ensure the correctness of a) their
interface to the control system b) logic written to coordinate and configure them. However,
such simulators are… Show more

Abstract Control systems for radio astronomy projects such as MeerKAT [1] require testing
functionality of different parts of the Telescope even when the system is not fully developed.
Usage of software simulators in such scenarios is customary. Projects build simulators for
subsystems such as dishes, beam-formers and so on to ensure the correctness of a) their
interface to the control system b) logic written to coordinate and configure them. However,
such simulators are developed as one-offs, even when they implement similar functionality. To mitigate this we leverage the idea of data driven software development and conceptualize a simulation framework that reduces the simulator development effort to: 1)capturing all the necessary information through instantiation of a well-defined simulation specification model 2)configuring a reusable engine that performs the required simulation functions based on the instantiated and populated model provided to it as input. Show less

Ensuring completeness and correctness of the requirements for a complex system is challenging. Current system engineering practice includes developing a stakeholder needs definition, a concept of operations, and defining system requirements in terms of use cases and requirements statements. We present a method that enhances this current practice into a collection of system models with mutual consistency relationships. It is a systematic approach to gather into one place the whole procedure of… Show more

Ensuring completeness and correctness of the requirements for a complex system is challenging. Current system engineering practice includes developing a stakeholder needs definition, a concept of operations, and defining system requirements in terms of use cases and requirements statements. We present a method that enhances this current practice into a collection of system models with mutual consistency relationships. It is a systematic approach to gather into one place the whole procedure of creating a system. The SDLC phases will be kept as a single silo of knowledge related and bounded by each other Show less