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Mastering the reliability of complex systems

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Many companies that develop complex systems, such as cars, luggage handling systems, robot arms, or lighting systems, are faced with:

  • increasing complexity: the number of failure modes evolve with complexity,
  • shorter development cycles: time-to-market (T2M) becomes even more important,
  • more demanding customers: they require even higher uptimes, and higher quality performance,
  • and the large impacts of warranty costs, penalty costs, and customer satisfaction on business results (sword of Damocles).

The challenge

One of the bigger challenges is to master the reliability at all levels with sufficient accuracy, that is at component level (hard and software), and (sub) system level for different use profiles (temperature, humidity, shock, vibration, corrosion, industrial gases, etc). Even further, the system needs to be controlled and maintained.

Seven requirements

In order to best respond to this challenge organizations need to comply with the following seven requirements. The basis for these requirements are many projects for multiple companies in the Netherlands.

  1. Processes and procedures for development, manufacturing, and maintenance geared towards supporting quality and reliability (DfR). See below an example of development phases, reliability activities and tools.CQM 1
  2. Testing, verification & validation: for substantial statistical power a large installed base is desirable.
  3. Highly trained and experienced reliability engineers (competence owner and local experts). Appoint a council of experts with appropriate decision power.
  4. Use of data science and smart analytics and deep understanding of the system and its use to support decision making and risk mitigation in all phases of the life cycle. Of course, availability of relevant degradation, failure and circumstantial data is key.plaatje 2 update
  5. Develop an easy to use & dedicated reliability calculation tool, that is applicable for your business. The purpose of such a tool is to:
    1. Automate the manual combination of proven reliability models.
    2. Prevent errors by rigorous data checking.
    3. Integrate the estimation of reliability figures during development cycles.
    4. Takes into account actual use profiles,
    5. Share knowledge.
  6. Continuous verification of the reliability predictions and models that involves:
    1. Life time testing in laboratories under controlled environments.
    2. Field evidence, which is vital for the verifications in application conditions.
  7. Compliancy with IEC regulations and beyond. You’d better strive towards “test to pass” instead of “test to fail“.

Resulting business opportunities

Suppose your organization is able to meet all requirements, what are the untapped opportunities for boosting your business? These are the opportunities we identified based on our experience and discussions with business leaders:

  1. Shape the market with reasonable reliability & warranty claims,
  2. Reduce CoNQ (mainly FCR),
  3. Reliability becomes a design parameter, and not an outcome. This will lead to design optimization and reduction of costs,
  4. Reduction of Time to Market (T2M),
  5. The ability to change your business model: from product to a system-as-a-service. You’re able to offer complex systems with a long-term contracts. The customer pays for the performance in terms of throughput, speed, uptime, service, energy consumption, etc.

If you have questions on this subject, please do not hesitate to contact Marc Schuld.

 

24 June, 2016 Marc Schuld

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Design for Six Sigma

* Process improvement strategies such as Six Sigma help to understand and tackle bottlenecks in the production phase in a structured manner. However, about 75% of production problems can be traced back to bad choices in the design phase. To guarantee high quality faster and with lower costs, it is therefore necessary to focus on statistical dispersion (variance reduction) starting at product development. By embedding the desired quality during the design process – Design for Six Sigma (DFSS) – we realize a cheaper process and shorter time to market! *

Define

This phase is about a clear project definition and getting support and approval for execution.

Identify

The main objective for this phase is to describe in more detail who the target customers are and what exactly makes them happy.

Design

This phase results in a high level design , the ‘product architecture’, for the selected concept.

Optimize

The objective of the optimize phase is to generate a detailed product design.

Verify

This phase focuses on the preparation for mass production and realizing the market introduction.

Monitor

In this phase, user, customer and stakeholder satisfaction will be verified.

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