What cannot be or is not measured, cannot be improved. Any data-driven approach for continuous improvement in manufacturing requires definition and ongoing tracking and reporting of key performance indicators (KPIs) against targets. This is as relevant in the boardroom as it is on the shop floor. What is the point in providing the tools and applications to steward manufacturing operations conformance against targets and constraints if the basic means aren’t in place to measure the operation in the first place?
Changing times: what was fit-for-purpose then may no longer be now
Many facilities were built at a point in time – some as far back as the 70s and 80s – for a particular process, a certain level of control and a certain suite of optimisation applications. Roll on to today where the world is grappling with the impacts of the COVID-19 pandemic. These facilities are now being operated and maintained at skeleton staffing levels and are being retooled for different services than were originally intended.
Operating envelopes are changing and the impact of these changes on instrumentation must not be underestimated. Instrumentation with a design rating of a particular flow rate or capacity is heavily stressed when the service or load is increased. In some cases, the instrumentation for the original service is unsuitable for the new service and needs to be swapped.
Some fine and specialty chemicals manufacturers may be dosing new chemicals into flowlines for enhanced process efficiency. For legacy instrumentation this can be a real issue as it affects the instrumentation resulting in periods of time when the plant is subject to sub-par control. This can impact plant safety and reliability, as well as profitability.
Key plant measurement considerations
Situational awareness forms the basis of effective decision-making in process facilities. The foundation for situational awareness is the plant data itself, gathered from the various devices on the front line. With context and relationship, plant process data measurements constitute information. Increasing context, connectedness, patterns/relationships and the understanding thereof, can then lead to knowledge and insight. This is fundamental to effective decision-making in plant operations, which is made easier through data analytics, which itself is under-pinned by the quality of the fundamental plant data. Only with robust plant data can the true potential of analytics be realised.
Three decisions to take today
1. Undertake a Value Of Information (VOA) audit
Knowledge and information are useless unless you are going to do something with it. While an excess of process data presents many opportunities, it can also paralyse an organisation and hinder speed of decision-making. Evaluate the key value drivers of the plant, assess which plant data and information is required to create value and then inventory the key instrumentation needed to ensure value creation can be sustained.
2. Instrumentation-related Management of Change (MoC) processes and procedures
Quality measurements must be maintained when switching between plant production levels or product line batches, as these stress instrumentation devices in different ways. Assign responsibility to an individual within the instrumentation discipline to work with operations for creating or updating formal Management of Change processes for key plant measurement/data considerations. Based on this, establish a fleet-wide measurement device monitoring and assurance program. A fleet-wide system for tracking and reporting performance, as well as assuring compliance, is a necessary first step to operational improvement.
3. Operations staff re-deployment
Where unit operations have been turned down, or temporarily shut, can those operators be re-deployed to support elsewhere in the plant? For example, regular and accurate pressure measurements and flowrates at either end of impulse lines on distillation columns are vital for a reasonably accurate mass balance to be achieved in order to match models to plant data. After all, many analytics and rigorous dynamic models use online measurements from the plant to provide information about the status of the plant that cannot be directly measured, can predict the future trajectory of the plant and advise the operators on action required to keep the plant within its operating window and at its optimum operating point. However, accessing these measurement locations isn’t always straightforward. Downtime of operations staff could be utilised to find sustainable solutions for these challenges for when operations ramp up again i.e. finding new ways to retrofit, upgrade or maintain measurements across the plant.
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