end-to-end engineering lifecycle: decoding the magic and

Brian SandersProduct MarketingJune 26, 2019

End-to-End Engineering Lifecycle: Decoding the Magic and the Myth

Engineering today’s smart, connected products requires sophisticated approaches to managing complexity.

IBM Watson IoT / © 2018 IBM Corporation


Requirements

Regulations

Reporting

Collaboration

Quality

Time to

Market

Costs

Products

Interfaces

Integration

Templates

Scalability

Digitization

Optimization

Innovation

Partnerships

Businesses face enormous pressure to meet the pace of

innovation in the era of the Internet of Things


Myths

• Essentially a process based on MS-Office documents & spreadsheets (or alike)

• What features/functions in spreadsheet/word processors are designed for managing complex product development

• Fragile and does not scale for complex products

• Pushing problems to later stages

• Very difficult to maintain consistency and traceability

• Miscommunication

• Challenge meeting compliance and regulatory requirements, internal and external audits, cost reviews

• Complexity of systems-of-systems, suppliers, partners Subsystem

Design

Implementation

Spreadsheets & Document work great for complex development

By 2022 25.6% of labor force will be 55-years-and-older(Bureau of Labor Statistics)

It's expected that by 2020, 31 million jobs will become available as Boomers retire, and another 24 million new jobs will be created. However, the population of younger workers with education and skills to replace Boomers isn't large enough or growing fast enough to make up for these departures, according to a Georgetown University report, which predicts a shortfall of 5 million qualified workers.https://www.shrm.org/resourcesandtools/hr-topics/behavioral-competencies/global-and-cultural-effectiveness/pages/4-ways-for-hr-to-overcome-aging-workforce-issues.aspx

Hire more systems engineers

• Institutional knowledge walks out the door every day

Aviation Week Survey 2017 tallied across Boeing, BAE Systems, Lockheed, Northrop that 18.5% workforce is eligible for retirement

Boeing offered early retirement to 9K senior employees and subsequent orders for 737’s threw production line into chaos given all the inexperienced employees they shut down production line costing $1.6B

• Experience trumps school every time

A petrochemical explosion occurred at a large plant on the Texas Gulf Coast, an investigation found that the engineers there at the time had all been on the job less than one year

Silver Tsunami

Requirement 1

Requirement 1.1

Requirement 1.2

Engineering Model

RequirementsModeling /

System Design TestCollaboration /

Workflow

Model

Plan Task

Source

code

Test

case

GAPGAPGAP

Individual engineering management products are best choice

➢ Develop and maintain interfaces long-term

➢ Handle all data incompatibilities, migrations, conversions

➢ Maintain single-source of truth, data integrity, audit/compliance trails

Integrated solution means lock-in

Systems Design

Requirements Management

Test Management

Workflow Management

Lifecycle Links

IBM Watson IoT / © 2018 IBM Corporation 9

9 of the 10 largest automotive companies

13 of the 15 largest Tier 1

automotive suppliers

9 of the 10 largest pharmaceutical

companies

8 of the 10 semi-conductor

companies

10 of the 10 major aerospace and defense

companies

54Government agencies

in 54 countries

13 of the 15 top electronics OEMs

9 of the 10 medical device manufacturers

Integrated engineering solutions are hard to learn/adopt

Al Gore created the Internet ?

The connectedness of everything and AI is transforming how businesses and the world work.

11

Accelerating innovation without compromising quality and safety requires a new level of sophistication.


Magic

What if your engineering teams could?

➢ Innovate with speed and quality while delivering mission/safety critical systems

➢ Meet regulatory, compliance, reporting & audit requirements (eg DO-178B, ASPICE)

➢ Drive constant improvement while dealing with increasing complexity across multi-tier value chains

Watson / Presentation Title / Date14

Engineering Lifecycle Management Solution

Advanced analytics and AI

Modeling and simulation

Seamless collaboration & open services/interfaces

Automation of compliance

Adoption of industry best practices & agile methods

Better understand customer requirements to improve product quality

Watson Natural Language Service and pre-trained AI, for writing complete, clear and testable requirements

Single source of truth for optimal collaboration across teams and teams-of-teams

Manage change across product lifecycle for faster impact assessment/better quality

Capture and manage traceability to tests and other engineering artifacts, including software to manage compliance

Best practices ensuring consistent terminology, customizable dashboards, quickly assess the impact of changes, drag-and-drop traceability

A single platform for managing requirements so your teams can work more effectively across disciplines, time zones and supply chains

Solution: Requirements Management powered by AI

Engineering Lifecycle

Managementwith AI

Visualize, analyze, and gain insight from engineering lifecycle data

Cross-discipline teams collaborate, share, review and manage designs and models using central repository

Prototype, simulate and execute complex systems for early validation of requirements, architecture, behavior

Creation of comprehensive documentation for specifications, communication, reporting and compliance

Automatically create system specifications, interface design documents and systems test cases

A structured and auditable approach to identifying requirements, managing interfaces and controlling risks throughout the project lifecycle.”

Solution: Model Based Systems Engineering

Manage the engineering complexity of systems of systems


Managementwith AI

Maintain quality while constantly delivering innovation

Risk-based testing prioritizing features / functions based on importance and likelihood or impact of failure

Collaboration through event feeds, integrated chat, review, and approval / automated traceability

Asses and monitor potential risks – enabling risk management to make predictions in line with requirements

Clearly portray project quality objectives and exit criteria, track responsibilities and prioritize items for verification and validation

Automate labor-intensive test planning, construction and execution tasks

Solution:

Build Quality in

Collaborative solution that offers comprehensive test planning and test asset management from requirements to defects, enabling teams to seamlessly share information using automation to speed project schedules and report on metrics


Managementwith AI

Orchestrate your teams workflow and communication to accelerate

development while ensuring quality and reporting consistency

EnablementBuilt-in work items and change-set traceability reduces

complexity of analysing what went into releases

Customizable portal views supporting multiple projects for seamless team collaboration

Model exact workspace of any build, developers can test their code against latest baseline

Engage suppliers as part of the development process to deliver higher quality, regulatory/compliance standards, and safety regulations

Automatically create and track progress of individual work items according to team’s agile, SAFe or custom process

A single platform for managing processes, tasks, and people so your teams can work more effectively across disciplines, time zones and supply chains

Solution: Manage workflow and collaboration across development teams


Managementwith AI

IBM Engineering Lifecycle Management (ELM)End to end engineering lifecycle management solution

Enabling a holistic end-to-end engineering development

process insuring teams are communicating & linked on

developing the best product they can while –

• Meeting regulatory standards

• Managing suppliers

• Achieving time-to-market

• Delivering on budget

• Passing audits

• Support compliance requirements

• Mitigate skill shortages

Why automotive OEM and suppliers adopt IBM ELM

‒ Establish an effective systems engineering practice to manage rapidly increasing complexity of car functions

‒ Accelerate introduction of new features and changes in a highly Competitive market

‒ Realize an end to end “digital twin” in the connected car era

‒ Accelerate compliance with key industry standard ASPICE and ISO26262 which strongly endorse MBSE as a core practice

As a result, more and more Automotive OEMs and suppliers adopt IBM ELM to mainstream the practice!

20


Why medical device manufacturers adopt IBM ELM

‒ Enable highly effective engineering providing early verification and validation of system specification and design choices

‒ Comply with functional safety to the standards like ISO 15288, IEC 62366 and/or ISO 14971 that require safety analysis performed on systems design and detailed documentation of the system design

‒ Managing complexity, amplified by regulations, integrations, and advances in technology, without compomising quality and time

‒ Address FDA’s finding that lack of design controls as one of the major causes of device recalls



Why railway companies adopt IBM ELM

‒ Compliance to regulations like EN5012x are becoming increasingly crucial in the Railway landmark. Model based approach significantly reduces the manual effort of compliance

‒ Early verification and validation, needed for CENELEC safety requirements, can be met by the left shiftcharacteristic of MBSE via simulation and testing ofthe system model.

‒ Traceability, assessing the impact of a design decision or change effectively throughinterconnected systems and subsystems, especiallyimportant for long term projectslike railway.

End to end engineering lifecycle management

IBM Enterprise Lifecycle Management

IBM Watson IoT / © 2019 IBM Corporation23

– Better requirements management to improve product quality and reduce ambiguity

– Meet regulatory, compliance, process, reporting & audit requirements

– Manage the engineering complexity of systems of systems and variants

– Drive constant process improvement while dealing with increasing complexity across multi-tier value chains

– Enable agile systems engineering practices

– Use operational data and customer insight to improve engineering decisions

Want to learn more?

Engineering Home Page:

https://www.ibm.com/internet-of-things/solutions/systems-

engineering?lnk=hpmpr_iot&lnk2=learn

MIT Technology Review: How IoT and AI

can transform engineering teams

https://www.ibm.com/account/reg/us-en/signup?formid=urx-37983

Agile Development Guide:

https://www.ibm.com/account/reg/us-en/signup?formid=urx-34954

Moving to knowledge-driven requirements

management:

https://www.ibm.com/downloads/cas/MDNWPEYQ

AI for Requirements Management:

https://www.youtube.com/watch?v=pXaKgAn7PJo&t=13s

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