How can the internet of things benefit manufacturers?

Big data from the internet of things provides great opportunities for manufacturers to improve product design and manufacturing.

The internet of things (IoT) is beginning to revolutionize how manufacturers of automotive, aerospace and industrial equipment design, manufacture and sustain their products. As these products become increasingly intelligent and connected, it is turning into a competitive necessity for manufacturers to “listen” to them and use the generated data to create actionable insights that inform product design. Although the process of becoming a manufacturer driven by big data analysis is far from simple, the potential benefits are vast.

How to harness the power of the IoT

The potential benefits of the IoT are huge for manufacturers, but to unlock its full value, three key components must be implemented.

  1. Data repositories and infrastructure
    To mine insights quickly from the vast amount of digital product data, manufacturers need a robust hardware and software framework, such as the highly innovative open source Java-based Apache Hadoop software, which rapidly processes large data swathes.
  2. Advanced analytics
    To create actionable insights from the vast amount of generated data, advanced analytics techniques are needed. These insights can improve product reliability and quality, and reduce nonconformance-related costs.
  3. Reliability engineering analysis
    Converting huge amounts of data into actionable insights requires the right tools. The primary tool for assessing potential impact and criticality of failures is product reliability analysis. Manufacturers can test the probability that devices will perform their function in certain conditions for a specific period of time.

Actions to undertake

  1. Establish a business-driven unified data environment
    Begin by creating a list of measurable questions your organization is trying to answer, such as “What systems have the greatest negative impact within the first 100 hours in service?” or “What sequence of events lead up to, or follow, a product failure?”
  2. Facilitate real functional alignment on product reliability
    Manufacturers may use many different data sources to establish product reliability-related metrics, such as warranty data or machine diagnostics. However, the key is to establish a single metric across various functions, providing a holistic approach to reducing D2C.
  3. Embrace product reliability
    Leading manufacturers have tools and processes that systemically create and manage relationships between a machine’s systems, components, software, service parts and onboard diagnostics that measure and detect any faults. Some manufacturers have been able to find issues months before they emerged as a detectable warranty claim.
  4. Close the loop
    Corrective action insights from advanced analytics need to drive the allocation of resources and investments to mitigate a product issue, whether in the design or manufacturing stage. Any root causes and corrective actions need to be fed back into the system, design, process and manufacturing to prevent future problems and improve the next generation of products.
  5. Don’t do it alone
    The process, technology and organizational changes required mean you could be best served by a third party’s guidance. Many leading manufacturers have had early success in this area by engaging various partners to assist in the development and deployment of the strategy.

 

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