Cloud or not? The best of both worlds for Industry 4.0
Bosch ConnectedWorld 2016 was a good place to sense hot topics and trends for connected manufacturing. Industry stakeholders gathered to discuss where the market is heading.
Towards an Industry 4.0 application store
Bosch recently launched its IoT Cloud and with it, the option of providing new Industry 4.0 micro services as the foundation for many new logistics and manufacturing software as a service (SaaS) offerings. The mechanism to dynamically deploy new services is provided by the IoT platform as a service (PaaS) layer. Next on the industry’s agenda is an Industry 4.0-specific application store, which will function as a self-service portal for users to source business-relevant apps and combine them as needed.
Cloud or not? The best of both worlds. Not necessarily a go/no-go type of decision
Production plants are often reluctant about putting their data in the cloud. Of course it’s a question of data security and IP protection, but it’s also a matter of context. It might not even be beneficial today to store data outside of the factory and use applications hosted in the cloud. In the context of monitoring data across the value stream however, multi-factory site data aggregation and integration will become necessary. Therefore, manufacturing experts are well advised to allow for the best of both worlds and cooperate with partners that can both host their data and applications in the cloud as well as deploy them on-premise to allow their IT team to operate them.
For example: When factory sites are gradually being integrated worldwide, monitoring tightening processes with a cloud-based process quality service can even be an interesting option for large systems and companies; and, of course, for SMEs with a small number of tightening systems. This allows both to improve on the quality of the production process and fully leverage the benefits of Industry 4.0.
Product variety + high capacity: combine it today!
It used to be that product variety killed high production capacity, but today, there are good initiatives for comprehensively guiding workers. Since staff will always play a decisive role in the connected plant, they need optimal support. Industry 4.0 workplace concepts include pick-to-light systems, interactive instructions, hand tracking (3D camera), product identification (RFID), and more. By combining order data and product data, an optimized task schedule can be generated for workers.
Complex production planning – made in China
One example of an Industry 4.0 software project that promotes the manufacturing of high product variance in automotive electronic products has been realized at a Bosch plant in Suzhou, China. A joint project was established to develop a software solution for streamlining the complex production planning setup (with high and low runners). It also manages clusters of highly parallel machines and lines to enable pool production for single steps in the manufacturing process.
End-to-end data mining services. Data is the economy’s new oil: use it!
In many Industry 4.0 projects at Bosch plants, data analytics already adds concrete value to improving the production process, e.g. by reducing test and calibration time or scrap. Data analytics will move towards a broader analysis – especially cross value stream – by using data from the supplier plants, correlating it with your own production data, and data from your customers. Moreover, cross lifecycle analysis will increasingly play an enabler role, analyzing data from all phases – making, shipping, using, and maintaining products – to optimize the other phases in each case.
Standardized data analytics? Go for it!
Very often, production data still goes unused today and is only taken into consideration for quality issues. The benefit of using data on a regular basis is to identify the right spots to continuously improve your manufacturing process. Advanced statistical methods help to understand cause-and-effect relationships between data and manufacturing output at the end of the day.
Applying customized analytics methods is just one option today. Another one is to increasingly use standardized manufacturing analytics tools as they have just started to evolve by providers such as Bosch – by combining data science, IT, and production expertise so you can fully leverage manufacturing analytics.
Building a bridge between the IT and machine worlds
Having a tool at hand for flexibly changing the rules for machines on a PLC base sounds new and interesting. At the same time, it might sound risky for operators. But what if there is no change to the machine program and no interruption for transferring the rules to the machine? Bridges such as the Open Core Interface (OCE/OCI) and web-based tools can be used to model production rules. The combination makes it possible to analyze the decision-relevant data of the machine during production and trigger appropriate events, for instance, sending an error report or a material order list to the service technician by email.
Which experiences do you have with practical Industry 4.0 implementations? Any key learnings or best practices to add? What are your thoughts on the cloud?