Services
IoT and Digital Engineering
Bringing Together IoT and Digital Engineering to Create Rich Experiences
Highlights
- Products these days are not how we’ve known them to be traditionally .They are becoming complex software driven systems of systems making it extremely challenging to manage their lifecycle.
- An integrated application lifecycle management (ALM) strategy that establishes the software digital thread is needed to address the challenges of multi-domain product development.
- Leveraging artificial intelligence and machine learning (AI-ML), cloud, and automation along with model-based practices can accelerate the delivery of defect-free software and ensure successful new product introduction.
On this page
The ‘software company’: A new role
Traditional manufacturers are turning into ‘software companies’.
Software defined products are driving innovation in every industry, from automotive to industrial machinery to healthcare. Managing the lifecycle of these products – right from gathering customer requirements to providing end of life support – has become challenging to say the least. While on one hand, manufacturers need to adeptly manage the development of these complex, multi-domain products, on the other, they also have to deliver continuous updates throughout the product lifecycle. With software features becoming the key differentiating factors, strengths in traditional product design and manufacturing alone will not suffice. Manufacturers need to rapidly scale their software development capabilities to stay competitive. They must also ensure that the software that accompanies their products is defect-free since the cost of recall can be significant. In this pursuit many manufacturing organizations are transforming into ‘software companies’.
Disconnected silos: The challenges within
Organizations typically grow by developing new lines of business, radically redesigning their products, or through acquisitions.
The software development environment in such a scenario typically grows over the years with tools and applications bolted on in an ad hoc manner resulting in a disconnected tool chain. In the case of acquisitions, the diversity of tools increases exponentially when companies using different tools unite. In our experience, such a disconnected landscape leads to several challenges like:
- Lack of visibility: There is no traceability between product artifacts such as requirements, test cases, design data, bill of material, and so on. This limits the ability to perform impact analysis before any change is introduced and limits visibility to the project progress, making it difficult to meet the targeted delivery timelines.
- Lack of collaboration: Software development teams have evolved into complex partner ecosystems comprising OEMs, sub system suppliers, and new stakeholders such as chip vendors and IP vendors. A disconnected environment cannot support the tight collaboration required among these partners.
- Susceptibility to errors: Managing the exchange of information across disconnected tools involves a lot of manual effort and is prone to errors. This reduces the efficiency of the development process, which in turn delays product introduction and increases the cost of development.
- Lack of reusable artefacts: New development programs often start by taking references from existing programs. But in a disconnected environment, project artifacts cannot be reused easily.
- Meeting regulatory compliance: High level of effort is required for ensuring compliance with industry standards such as Automotive SPICE, ISO26262, and SOTIF. Stakeholders spend manual efforts to collect review and approval evidence for compliance audits.
The digital thread: A connected software ecosystem
The transformation of a disconnected software development ecosystem requires harmonizing the tools and processes into an integrated framework, leveraging cloud, AI-ML, and automation.
A software digital thread spanning the complete V cycle of development must be established to enable seamless data flow across stakeholders. It must also provide contextual visibility of development processes and artifacts for accelerated decision making and reduced cost of development.
We outline the tenets of this approach:
Value chain connectivity
The product development process must be implemented on an integrated tool chain that can enable traceability across the lifecycle. It should enable methods standardization, tools integration, and process harmonization. It should be integrated with system and software modelling tools, hardware-in-loop (HIL) platforms, continuous integration (CI) solutions, product lifecycle management (PLM) systems, reporting and dashboarding tools, and more.
Model-based development
Model-based work practices and methodologies must be adopted to drive the complete multi-domain product development. With a model-based approach, overall development focus gets shifted to the ‘left and top’ of the V cycle, leading to reduced verification and validation efforts.
Product line engineering (PLE)
A feature-based or platform-based approach of product line engineering must be adopted to enable the reuse of project artifacts such as requirements, models, test plans, code, and more, across multiple product programs. This helps stakeholders to jump start a new program and improve overall product development agility.
Technology levers
The software digital thread lays the foundation for leveraging advanced capabilities of technologies such as cloud, AI-ML, GenAI, and automation automation.
Cloud
Cloud-based software development, verification, validation, and deployment reduce the dependencies on physical hardware and hardware in-loop (HIL) platforms. Leveraging cloud with containerization can enable virtual validation and establish cloud-based ‘test benches-as-a-service’, vastly reducing the cost of testing.
AI-ML and GenAI
AI-ML models can be used to extract intelligence and accelerate the development process. For instance, new product requirements or validation scenarios can be extracted from actual product usage data, thus reducing human error. GenAI solutions can be developed for defect trend analysis or identification of potential issues in the field.
Automation
With increased compliance norms, there is an exponential increase in validation requirements. Validation automation is the only way to accelerate the validation cycle. This can include validations like software-in-loop (SIL), model-in-loop (MIL), and hardware-in-loop (HIL).
The road ahead: Leading the charge
For a sustainable competitive advantage, enterprises will have to revolutionize the product development process – and digital thread holds the key to this transformation.
With the future of products becoming complex software driven systems, the ability to scale up software delivery at an accelerated pace and competitive costs, while also ensuring first-time-right designs is going to be the key to winning in the market. We are of the view that embedded software lifecycle management services will help organizations define the strategy, establish the roadmap, and deploy these capabilities to ensure a successful transformation.
Per our analysis, establishing a future-proof foundation through the integrated framework, adopting a model-based approach, ensuring reusability, and leveraging automation, AI-ML, and GenAI are going to distinguish the leaders from the rest. A software digital thread built on these core tenets is the right strategy to transform the ALM ecosystem for manufacturers of software defined products of the future.
