wilamowski-b-m-irwin-j-d-industrial-communication-systems-2011

Process Automation 25-9
challenging as process plants incorporate a large investment. Therefore, new means are necessary that
allow utilizing production facilities for different products and allow fast switches between products to
be produced. For such systems, [GNP94] coined the term “agile manufacturing.” In order to provide
such manufacturing systems, the dynamic reconfiguration of plant structures as well as the control
software is required. Parametric changes are not enough as they lead to unmanageable control software
modules. Fifteen years later, recently conducted surveys such as the MANUfuture Strategic Research
Agenda [EC06], which is one of the platforms that are integrated in the definition of the frame programs
of the European Union, claim the same objectives.
Multipurpose facilities built in the above described network plant structure provide the demanded
flexibility and adaptability from the mechanical/physical point of view [K99]. In order to operate such
plants effectively and efficiently, new ways for the control structure have to be used. Distributed control
with its control nodes locally attached to the plant controlled part represents such a means. Distributed
control architectures allow localizing changes and disturbances in the plant. This helps to keep changes
manageable for the human as not the whole system has to be investigated. Furthermore, distributed
control systems feature an increased scalability allowing to add or remove plant parts. First works on
this topic were able to show these benefits, e.g., [LZ08,PCSK07,SSPK06, and TSPK07].
Distributed control systems are an important foundation for flexibility and reconfigurability of production
systems. However, in case of changes, disturbances, plant failures, or adaptations, labor-intensive
engineering work is necessary. Therefore, more autonomous technologies are needed in order to
reduce the human effort incorporated in production changes, as the human effort needs time (i.e., costs)
and is typically error prone. A possible approach is to enhance the distributed control modules with
autonomous cooperative functionalities. These allow the unit to provide its functionality (e.g., process
reactor) to the production system and cooperate with other units like pipes, valves, pumps, or other
process reactors in order to fulfill the overall goal production. For assembly automation, several such
approaches were investigated and tested (see for example [B06,LR06, or VMM08]). They were able to
show that the flexibility and adaptability of the plant is increased. More research is nevertheless still
needed in this area before these concepts can be applied in industrial systems, especially for process
automation where only little research has been done.
These new paradigms do not change the general production information exchange as described
above; however, they change the overall structuring of the control system’s architecture and therefore
also the ways control components interact. The hierarchical structuring as shown in Figure 25.1 will be
broken up into a network oriented one. Therefore, the control architecture resembles the mechanical
structure of a flexible (batch) process plant. This leads away from the currently employed request/reply
(e.g., client/server) interaction to a peer-to-peer interaction. Future control components will be equal
members of the production system and interact with each other on a negotiation basis. However, as
process automation systems interact with the real world, there are different kinds of interaction on different
levels with different properties. On the higher levels, there are the negotiations between control
components in order to fulfill the overall task production. These negotiations feature a higher amount of
data but are in general less time critical. On the contrary, on the lower interaction levels—the real-time
control levels—the communication’s task is to synchronize the control algorithms. For this purpose,
we encounter short messages that have to be transmitted and processed in real time (see Figure 25.4).
Communication systems for upcoming process automation systems, therefore, have to support the peerto-peer
communication of equal distributed control components. This communication has to be flexible,
allowing changeable communication relations and also support real-time interaction as needed by
the real-time control elements.
Current communication systems for process automation are developed for the hierarchical command/response
or master/slave paradigm as applied in today’s process automation systems. These
systems are not suitable for the upcoming needs of distributed control and autonomous production
resources. Therefore, new communication systems have to be developed in order to support the new
paradigms.
© 2011 by Taylor and Francis Group, LLC