466374 Scheduling and Internet of Things - Vision or Reality?

Tuesday, November 15, 2016: 5:28 PM
Carmel II (Hotel Nikko San Francisco)
Iiro Harjunkoski, Process and Production Optimization, ABB Corporate Research, Ladenburg, Germany

In the last decade there has been an increasing discussion around the topic internet of things (IoT). In fact the term was first coined by MIT in the late 90s and refers a world where objects are connected, monitored and optimized through either wired, wireless or hybrid systems (Zhou et al., 2015). As a consequence there are academic-industrial activities world-wide e.g. Smart Manufacturing in the US and Industry 4.0 driven by Germany. The term cyber-physical system, originating from the area of mechatronics, refers to a system composed of physical entities such as mechanisms controlled or monitored by computer-based algorithms. Even if the first actual developments have been done for discrete manufacturing, this opens up lots of interesting application opportunities also within chemical processes.

From a supply chain management perspective, IoT should enable automated decision making reducing the need of human intervention. Connectivity is one of the key issues here since it is predicted that there will be around 50 billion connected devices already in 2020. Much attention has been paid on mainly three elements: Big Data, Cloud computing and Cyber Security. These are natural areas of research since increasing connectivity also multiplies the available data, of which a large part is unstructured (Babiceanu and Seker, 2016), the data processing is by itself a challenge and the value or outcome of it is unclear. Cloud computing offers means for hosting and analyzing larger set of data collected from various sources and in this context the security of data becomes an issue - also within an intranet. Thus, data is one of the key enablers of new applications and it is expected to improve the enterprise, manufacturing and business decision support. It is expected that having more information about the processes improves their resilience, i.e. the capability to cope with complex events and respond in acceptable time. This following the vision of providing physical components awareness of the context in which they operate to enable more independent decision making in a collaborative manner. Even though the IoT-focus is also moving towards mobility (5G) etc., the realization of "smart space", where users can easily enjoy a variety of services at any time and any place, is still in its infancy (Shen et al., 2015).

The fact that developments have been lead by the discrete manufacturing does not mean that it has less potential within the process industry. Maybe even the opposite is true but the more complex physical processes and established and installed solutions evidently slows down the realization of the IoT scheme into its full scale. Furthermore, before agreeing to a mainly SW-driven change, process industries should also be able to see the expected value. Successful use cases are still few and therefore the IoT-activity is often seen as a technology push. While some opportunities may be realizable in short-term, it can be expected that in long term the well-established automation pyramid (Engell and Harjunkoski, 2012) will dissolve. This has a severe impact on current process control and scheduling technologies as the hierarchical structure is replaced by an any-to-any communication increasing the opportunities for collaboration and especially through better tracking make it possible to adapt the schedules on-the-fly. Having faster and more flexible communication channels across business systems also enables totally new business models and new vendors to enter the market.

Nevertheless, the basic function of and need for production scheduling will certainly remain, as it is important to be able to coordinate and manage a network of physical processes in an economical, safe and energy-efficient way. The IoT development makes the role of scheduling even more important part of an intelligent manufacturing environment (Li et al., 2015). The vision of being fully able to track production, use historic and current data to predict possible incidents and re-schedule the production including maintenance operations in order to avoid incidents before they actually occur and ensure that the production is always done in the most optimal way will one day be technically realizable. Before this can become reality, there are still many obstacles related to communication standards, cross-interactions and conflict handling but also in the modeling and solution of the resulting problems. This presentation aims at catalyzing the discussion on the real obstacles and needs to bring the IoT-vision into reality. Some of the key questions are: Do we need IoT in the first place and does it bring added value and are the conventional approaches sufficient to meet the upcoming challenges?

Zhou, L., Chong, A.Y.L., Ngai, E.W.T. (2015). Supply chain management in the era of the internet of things (Editorial), International Journal of Production Economics, 159, pp. 1-3

Babiceanu, R.F., Seker, R. (2016). Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook, Comput. Industry, http://dx.doi.org/10.1016/j.compind.2016.02.004

Engell S., Harjunkoski, I. (2012), Optimal Operation: Scheduling, Advanced Control and their Integration, Computers and Chemical Engineering, 47, pp. 121-133

Shen, F., Liu, L., Palesi, M. (2015). Introduction to the special issue on "Emerging research in Internet of Things" (Editorial). Computers and Electrical Engineering 44 (2015), pp. 104–106

Li, G., Ge, Y., Wang, Y., Hu, S. (2015). Job Scheduling Management Research of Intelligent Manufacturing Based on the Internet of Things, Chemical Engineering Transactions, 46, pp. 829-834

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