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Ashok Pershad

PROCESS ANALYTICAL SPECIALIST, CENTRAL LABORATORY DEPARTMENT, EQUATE PETROCHEMICALS

With MBA in Operations, and Engineering Degree in Instrumentation & Control, Ashok has started his career with ABB limited, India as Analyzer Engineer (Projects) and then with SABIC, Saudi as Process Analyzer Engineer. At present he is working with EQUATE Petrochemicals, Kuwait as Process Analytical specialist where his main area of expertise is management of Quality Results for Process Analyzers and at the same time optimizing the deviation between Process & LAB analyzers results.

LAB & Online Analyzer’s Results Optimization (ABCs to Quality Results Management)

Process Analyzers – Emerging Trends and key Factors for Successful Implementation

Abstract: We often seen many plants where we are sending lot of samples to Laboratories (LAB) in order to control the process. At the same time, we have Online Analyzers installed in the field for same purpose. Now the question comes which one to believe in case we get deviated results from both LAB & Online analyzers. Most of us believe LAB as final authority where results are always perfect. Has anyone ever thought of the kind of money, resources and time we are spending while waiting for the LAB results, which we could have get in case the Online Analyzers results are reliable? However, I totally agree in some plants, the situation is another way around where Online Results are more reliable as compared to LAB but when it comes to final product quality or product shipment then LAB is always right. The Question remains same, which one is more reliable. In particular, this paper will look into two technologies that are same but used in different scenarios where proper integration can help plants to control the process in defined manner and save big bucks. It talks about three processes (A, B & C). Each process has its own set of measures and are interconnected in some way to each other. Process A defined for LAB, Process B for Online Analyzers and finally process C for integration of process A&B in order to get controlled/optimized results from both processes.

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