IIC Journal of Innovation 4th Edition | Page 45

Outcomes, Insights, and Best Practices from IIC Testbeds: Track & Trace Testbed employ analytic experimentation throughout the stack to decode the data and apply it in a way that was meaningful for the enterprise. As more and more data is collected, data scientists work with the data, build data models and compute the data. This complex and ongoing effort of the data scientists is not something easily standardized. model, there are no currently existing standards. The Track and Trace Testbed team has developed a data model which has been standardized within SAP. Having a common data model gives flexibility, but it also enables the standardized structure to be applied to other current and future use cases. This standardization has enabled the testbed team to develop a solution quickly. An interesting discovery in the midst of this testbed was the importance of a team approach: A team must come together because there is no individual who can solve all of the issues. Technology integration is necessary because more than one technology is essential to fulfill all of the requirements. So technologies are combined on the factory level. The team works together with data scientists, IT experts and process experts to develop the models to interpret the data and deliver the business benefit to the customer. The Track and Trace Testbed is a joint effort with regular meetings conducted with IT scientists from Bosch and SAP, business partners directly from the customer plant and technology partners. For data and communications, there are many standards. The data and communication of the testbed is more challenging and is still under discussion. The forklift team may leverage an existing standard and is currently evaluating which data and communications standards will be most useful to the testbed. It is not easy to figure out the best standardized way to exchange data between these two worlds: messages and protocols and within the technology. Communication standards exist and the testbed team is looking into standards (such as MQTT) for communications purposes between devices and the back end, identifying the right standards to apply for the testbed’s communications purposes. Experimenting to Determine Standards There are many standards related to the factory tooling aspect of the testbed, such as CIT, HCT, among others. But a layered perspectives on API standards is currently missing. The Track and Trace Testbed team must experiment at every stage to determine which standards to apply, whether an existing standard need changes and whether their efforts are relevant for the future. This is time consuming and requires careful discussion and evaluation. When working with standards, there are two steps: first the team applies the data model standard to the solution they have developed. This they sell that solution to the customer, enabling the customer to achieve the benefits of the data model. Then the There are two standards categories at play within the Track and Trace Testbed: the common data model and the data in communication. For the common data 44 June 2017