Improvement practices in process industry—the link between process control, variography and measurement system analysis

Abstract

In modern process industry it is necessary to find " smart " ways to continuously satisfy customers' demands, strive for more efficient production and prioritise the focus on safety, health and environment, allowing dedicated companies to obtain a competitive advantage. To achieve individual goals in these areas, companies increasingly implement a so-called business system approach, which ensures systematic, continuous improvement initiatives in all sectors. Most business systems address improvement in process control, since in many cases there is a significant positive economic potential which often only requires minor capital investments. This is also the case for Glencore Nikkelverk, Norway, where it has been decided to transform a former project-based improvement framework into a holistic business system, the Nikkelverk Business System (NBS). One pillar consists of different tools to improve process performance, with the objective to identify critical processes and process stages a.o. and also to ensure that the measurement systems in use can be geared, and validated, to mainly capture process variations, allowing to document valid process improvements. At Nikkelverk there are between 6000 and 7000 measurement points, of which one-third are used for process regulation purposes. It is therefore critically important to be able to monitor and verify that measurement system uncertainty is suitably low—ideally at a level of 10% relative or below compared to the variation of the process being monitored. This will become a key priority. An optimal measurement system should therefore not contribute significantly to the total apparent process variation as revealed by raw process data that are used to track when a process is deviating from steady state or dangerously close to control limits, or gets outside relevant safety limits. Critical processes must be kept under constant monitoring and control to ensure that all improvement attempts work from a solid database. As but two examples, energy and material consumption, can be fine-tuned to a lowest possible level only when both processes themselves and the measurement systems are monitored and controlled properly. This not only contributes to the cost efficiency of the company, but enforces process monitoring and control to take a leading role. We here focus specifically on the relative merits of variographic analysis (Theory of Sampling) and measurement system analysis (Six Sigma) and show how the former can function as a very effective screening for the much more costly latter. Historical background S ince the 1930s, processes have mainly been monitored by con-trol charting, starting out with the well-known Shewhart chart, a concept of quality control in manufac-turing which was first advanced by Walter Shewhart. 1–4 Many graphical methods have been developed under the umbrella of " sta-tistical process control " (SPC), for exam-ple the Quesenberry chart, Moving Range chart, EMWA chart etc., which all have the purpose to make room for the voice of the process. But with such a wide range of possible methods, one can at times be bewildered instead of informed. It is quite a task to find suitable (and simple) tools that give you good enough results to work on for continuous improvement of key processes. It should not, however, be necessary to be an expert in statistics to be able to improve an industrial process. Tools and methods used must be relatively easy to grasp for process technicians, enabling involvement of as many stakeholders as possible to create a common understanding of the current process state. Hence the best analysis is the one that provides the great-est insight with the simplest approach. But this organisational challenge will not be fur-ther discussed in this paper, which instead focuses on two salient technical issues, measurement system analysis (MSA) and variographic process characterisation.