Systems engineering software and solutions
Scale your engineering processes with AI-driven insights across the product lifecycle
Scale your engineering processes with AI-driven insights across the product lifecycle
Today’s software and product development teams are tasked with creating offerings that are of high quality, meet safety-critical compliance and regulatory standards, are price-competitive, and are delivered quickly.
The solution is to adopt a pragmatic approach to managing the development — from requirements and modeling through development, product testing and release. Maximizing effectiveness requires an end-to-end view across the entire product lifecycle for all stakeholders.
Adopting an end-to-end solution for the product and software development lifecycle makes it easier to coordinate multiple work streams and collaborate/communicate across all stakeholders, including suppliers.
Keeping dispersed teams connected, enhancing real-time collaboration, automating repetitive tasks and improving traceability across the entire development lifecycle helps increase productivity of the development team.
Leveraging the visibility provided through and end-to-end approach enables transparency and traceability from requirements through testing. Continuous testing, improved change management and less rework lowers risk and improves quality.
Adopting a more agile approach to managing product and software development enhances productivity of your engineering teams, lowers costly late-cycle rework and improves overall product quality.
Leveraging a single source of engineering data and processes, along with traceability, provides a strong foundation for validating compliance and documenting development status.
Being able to generate reports to understand the source of issues, communicate the status of the project and define areas of potential process improvement will help reduce cost, improve quality and ensure on-time delivery of products.
Requirements management serves as an essential practice and framework for product lifecycle management. It controls project scope, saving time and money. It also drives better insights for product development, with enhanced traceability and improved collaboration.
As product complexity grows, so does the need to provide better model-based systems design. MBSE lets diverse teams collaborate to analyze requirements, optimize design decisions and validate functionality. Plus, teams perform design reviews and automate delivery.
Enabling effective collaboration in real time is critical for success across dispersed, multi-disciplined teams. Proper workflow management offers an open architecture for collaboration, a streamlined agile development model, and automation of governance.
Quality management creates benefit opportunities, but collaborative, web-based tools for comprehensive test planning are needed to boost product quality. Integrated test solutions provide extreme clarity for immediate feedback, maximum efficiency and reduced cost.
IBM engineering lifecycle optimization offerings expand standard ALM capabilities with enhanced functionality for analyzing engineering data, managing processes, establishing best practices, generating custom reports and managing third-party integration adapters.
The IBM ELM Tools Suite – Base bundles three key components of systems and software engineering management: requirements, testing and workflow management. This bundle effectively provides the foundation to establish a holistic development management environment.
The extended IBM ELM Tools Suite bundle provides an expanded development management environment through five key components of systems and software engineering management: requirements, testing, workflow management, systems design and engineering data analysis.
Systems of systems, teams of teams. What else does the future hold? The International Council on Systems Engineering looks ahead.