Development Practices for the IoT Era

The Internet of Things (IoT) is not just about connecting things to the Internet and controlling them remotely. It is a major opportunity for developers of things (makers) and operators of things to unlock new value propositions from the lifecycle of things, and to improve innovation and the quality of things. In our context, things are products such as automobiles, medical devices, consumer goods, factory machines, etc. To leverage the value of connected and instrumented devices, there are several important aspects to consider, one of which is a proper digital product development process. Also, it is no longer a secret that in today’s advanced products most of the innovation comes from the embedded software, so the effectiveness of the software development process is an important parameter of the overall product development process.

Here are some key leverage points of connected products:

• It is possible to continuously collect operational data from devices when in operation.
• It is possible to remotely update the software that is embedded in the products.
• With the addition of social media, product makers can also get continuous information on how products are used in different market segments.

However, to leverage such enablers, product makers need to change their traditional development processes. The development processes need to be much more dynamic and agile to leverage the connectivity and advanced engagement of connected products. Here are some key transformational aspects for the development process:

Connected product complexity—Complexity is increasing with the additional functionalities provided by new interactions between products and product to cloud. Practices for handling this complexity rely on digital systems engineering processes that are based on digital representations of product requirements, product architecture, and product verification plans. Such digital systems engineering approaches enable continuous verification of product designs to eliminate risks early in the process as part of addressing this complexity. Continuous verification utilizes techniques such as simulation and rules-based checking to validate the requirements and the system architecture.

Transforming data into engineering insight—The amount of operational data available from connected systems is overwhelming and typically engineering information is locked in isolated silos. Data coming from operations and manufacture may trace to product requirements, product design, and product test. Being able to properly analyze all those product engineering aspects requires complete digitalization, traceability, and analytics of all product development aspects.

Increasing speed of development—The connected world increases the need to respond much more quickly to market findings and demands. The ability to effectively respond to change in multidisciplinary products depends on an effective change management process, where impact analysis of the change is conducted in a completely digital manner based on query across lifecycle data. It also relies on the ability to create change contexts across the lifecycle, without interfering with the overall system state before the change is actually approved. Creating such change contexts is enabled by configurations across the lifecycle.

Specialization—With the advancement of social media around connected products there is going to be higher demand to create more specialized products to deal with competition and optimize product revenue. That requires capabilities to properly manage reuse and variation as part of the product development process. Ineffective ways to manage variation limit the ability of product makers to effectively leverage product variation.

Streamlined process with continuous integration—IoT architectures require both proper support for embedded software that can be updated on devices, as well as software on cloud that analyzes and controls devices.

In order to achieve this transformation of the engineering development process, customers should look to the IBM Internet of Things Continuous Engineering Solution. The IBM Continuous Engineering (CE) platform, which is based on the Rational solution for Collaborative Lifecycle Management (CLM), provides the infrastructure and capabilities to enable a digital engineering lifecycle, which is necessary to meet the challengse of rapid and effective multidisciplinary development. Any activity and artifact as part of the process are digital and cross-linked—whether those artifacts are requirements, product designs and architectures, test plans or change history. There is no need to rely on traditional documents in the process, which are typically the main blocker for digitalization of the lifecycle. Open, standards-based lifecycle data indexing, query, reporting, and analysis are also key to effectively supporting the stream of incoming changes as part of the connected lifecycle. Recent updates to the CE platform now provide the new capability to define cross-lifecycle configurations, enabling parallel work on new innovations as well as effectively handling product variations by efficient reuse.

To summarize, the new generation of connected products that makes the Internet of Things is a major opportunity for product makers if they properly adapt their product development practices to leverage the opportunities and meet the challenges. As already identified by some key IoT-related initiatives, such as  Industrie 4.0 in Germany, and Industrial Internet of Things (IIoT) initiatives in the United States, the required transformation is to shift product development to a digital platform.