InTech

MAY-JUN 2019

Issue link: http://intechdigitalxp.isa.org/i/1124215

Contents of this Issue

Navigation

Page 18 of 55

INTECH MAY/JUNE 2019 19 PROCESS AUTOMATION tor is less and less involved in the inner control loops with direct contact to the process. The tasks shift more and more to supervisory control, where the op - erator manages and supervises a large number of control modules. Bridging the knowledge gap But being less involved in direct process control also means fewer opportunities to develop a feeling for the process by training on the job. (This problem was dramatically illustrated with the ac- cident of flight AF447. The autopilot discovered inconsistent speed mea- surements from all three redundant speed measurements and switched into manual mode. The pilot did not have enough experience flying at great heights and was overburdened with this sudden and unexpected transfer of responsibility. He went into climb mode, which reduced the speed of the plane and finally led to the crash.) To be able to take over when auto- mation fails, operators need higher qualifications and a profound under- standing of the technical process, the automation system, and the control modules. Simulator training is neces- sary to develop a feeling for the pro- cess. Modern operators should also be deeply involved in the optimization of process operations, because such an activity keeps them involved and helps to build up the required knowledge that allows them to take over in case of automation failure. Another area where Industry 4.0 will have a huge impact is industrial qual- ity control. Big data techniques make it possible to distill historical process data into algorithms that can predict the quality of the currently production. Up- coming problems can be detected early, and countermeasures can be taken be- fore the effect of the problem becomes significant. Previously, it took an opera- tor many years to accumulate compa- rable experience. Remote expertise should be brought in for all complex and difficult decisions (figure 3). For example, in the case of the Deepwater Horizon oil spill, the investi- gation report clearly states that one ma- jor factor contributing to the accident was the incorrect interpretation of avail- able measurements. Quite likely, with advice from highly qualified remote ex- perts, the company would have avoided this accident. The high complexity of modern plants requires expertise from many different domains (e.g., MPC, chemistry, electri- cal drives, distributed control systems). It is impossible for most plants to hire personnel with sufficient knowledge in all these areas. Modern collaborative environments make it possible to bring in remote expertise as needed. Managing key performance indica- tors for process operations in areas such as control loop performance, alarm management, energy efficiency, and overall equipment efficiency is not a classic operator task but is becoming more and more important to ensure good production performance. Disci - plines such as operations, maintenance, and analytics need to go hand in hand to achieve best results. Many of the tasks either can be performed by centralized internal service centers or can be out - sourced to specialized external service providers. Typical goals are increased through- put, efficiency, and uptime for the pro- duction plant. These goals are accom- plished by a structured approach to revealing the sources of process varia- tions and upsets and how they are cur- rently handled. By reducing process variations, organizations will increase the operational flexibility, plant regular- ity, safety, and integrity, while reducing off-spec production, energy costs, envi- ronmental impacts, operator stress, and equipment wear. For example, Dow Chemical intro- duced a global analytics layer that turns vast amounts of data into information and metrics anyone could see. Experts from a centralized Analytical Technology Center can now support plants globally Figure 3. Modern operators should be deeply involved in the optimization of process operations, because such an activity helps to build up the required knowledge that allows them to take over in case of automation failure. Remote expertise should be brought in for all complex and difficult decisions. To be able to take over when automation fails, operators need higher qualifications and a profound understanding of the technical process, the automation system, and the control modules. Time Process performance potential 100% Phase 1 Diagnose (fingerprints) Ideal Auto Manual Phase 2 Implement Holistic control room working environment Performance gap Phase 3 Sustain (ProcessPRO)

Articles in this issue

Archives of this issue

view archives of InTech - MAY-JUN 2019