Complex logistics. Production processes often are distributed over vast areas and require movement of large quantities of material both within the production facilities and between sites.
In recent years, most of the return on investments in business-to-business (B2B) has come from marketing and sales (the so-called e-commerce). However, e-commerce has a limited impact on the chemical industry, because so few customers and suppliers are involved in the supply chain. The true impact of B2B in this sector appears to be related to integration of production with logistics services.
If the constant increase in autonomy is key to the evolution of industrial automation, the leading concept for contemporary business is agility. A business is considered agile when it is able to interact advantageously with global markets, adapt to their continual variations and produce high-quality goods/services oriented to the peculiarities of individual customers. If the chemical industry is to benefit fully from the opportunities offered by Internet-related technologies, its production processes must evolve from the "sell-from-stock" mode to the "make-to-order" mode. Fig. 1 shows two typical situations in which an easily reconfigured production setup makes all the difference.
Figure 1. Chemical Industry Production Challenges
Production processes must evolve from the sell-from-stock mode to the make-to-order mode.
Automation and control are not merely a question of management software or sophisticated mathematical algorithms. Instrumentation that interacts with the physical world ," meaning sensors and actuators ," plays a fundamental role and will continue to do so in the future.
Many future advances will depend on the ability to accurately and reliably measure the physical-chemical values of the systems to be controlled ," acquiring increasingly detailed knowledge of the process. Higher production efficiency, lower emissions and a greater degree of safety require the use of ever more sophisticated and precise sensors.
The very concept of sensors currently is being revised and expanded. Instead of building on a single physical device, some sensors contribute to networks of instruments and/or software programs that are able to exploit analytical redundancies to correct and increase the reliability of existing measurements or to estimate new ones.
Intelligent sensors connected by field buses, inferential sensors, and self-calibrating and/or self-compensating sensors will be key factors in process automation in the coming decade. More precise and cheaper sensors can be placed throughout the plant to produce more complete data for better production optimization. The wide-scale introduction of sensors of various kinds within the automobile industry is a clear precedent: A further lesson that can be learned from this sector is that economies of scale can reduce associated costs drastically.
The increased use of sensors now allows better and more reliable environmental monitoring to rapidly identify sources of pollution. In the same way, preventive and predictive diagnostics will become more effective, especially for tasks that are not currently possible.
Another area that stands to benefit from better sensors is asset management. Networks of dedicated sensors can promptly identify components and/or materials that are not used to their full potential. They can also replace or repair critical elements as soon as signs of malfunction are detected or before they jeopardize either safety or production continuity. However, all these tasks require not only better sensors, but also better and more careful integration of the sensors within automation systems.
The computer infrastructure
The situations depicted in Fig. 1 require almost instantaneous decisions based on reliable real-time information concerning the plant's status and availability. This scenario is made possible only by the presence of a suitable computer infrastructure connecting the separate worlds of process control and enterprise resource management. Information flows from each single device in the field to the management offices (called device-to-enterprise [d2E]). Numerous applications function in synergy, drawing information from a single data repository.
This dual function is effectively performed by modern process information management systems (PIMS). PIMS:
Interface the various control and basic monitoring systems to gather process data, with sampling times of a second or less.
Integrate the data gathered into the real-time databases.
Convert all significant values and store them in large, efficient relational databases that permit sophisticated off-line analyses.