Understanding the story behind the data

Posted on 17 Oct 2015 by The Manufacturer

Making sense of vast volumes of production data is the essence of asset optimisation, says Nick Milner, director of professional services at AspenTech – a leading provider of smart manufacturing and supply chain management software, and services for the process industries.

If you can’t see what you don’t know, you won’t be able to make the right decisions to optimise production and be competitive.

Nick Milner AspenTech
Nick Milner, director – professional services, AspenTech.

The inside story of operational intelligence lies in rich thin visualisation and analytics capabilities that improve production execution, enabling process manufacturers to quickly identify and resolve operational issues.

The challenge for many process manufacturers today is to improve the analysis process and incorporate product characteristics and other non-time series data, along with the usual sensor and meter data being collected by the process historian.

It’s those data elements that provide additional context for an improved understanding of conditions that limit production operations.

Cutting-edge manufacturing execution systems (MES) integrate the operation, using real-time business performance management to optimally plan; execute; monitor, and respond to change immediately across all time horizons.

Information must be relevant, timely and collaborative. With discoverable data displayed in a clear, easy-to-understand dashboard, process manufacturers can efficiently resolve operational issues to remain profitable.

Identifying the problem

Production analysis often lacks the ability to visualise data in flexible formats, or incorporate operational characteristic data quickly to identify and correct the root causes of operational problems.

Analysis of production events allows manufacturers to analyse multiple responses to operational events and adopt best practices to further optimise operations.

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To gain a thorough understanding of the asset and its performance requires powerful data visualisation technology, which can put plant information into context.

Accordingly, operations personnel can apply timely corrective actions to address important operational issues, like bottlenecks; yield efficiency; variability in product quality, and overall asset effectiveness.

Visualisation techniques are mainly appropriate for the three types of variability in batch or event processing: average over time, within-batch/event and batch-to-batch/event-to-event.

Event data has been difficult and time-consuming to incorporate in data visualisation in the past. Significant time and effort was required to find, extract and include non-time series data like product characteristics previously. This effort has been significantly reduced in modern production visualisation solutions.

Modern manufacturing is like an ecosystem of interconnected software and hardware that helps companies optimise plants and achieve operational excellence.

As businesses generate vast amounts of data, efficient decision support solutions are needed to make sense of vital information and ensure operations can adapt quickly to dynamic conditions.

Understanding the data

Automated MES decision support allows manufacturers to make corrective decisions faster to achieve operational efficiencies and deliver greater productivity.

Bridging the gap between the technical operation of the plant and the commercial transactions using the latest digital environment (i.e. combination of web, mobile, tablet), MES provides users with the right information at the right time, allowing staff to dynamically keep up-to-date with operational challenges, anytime and anywhere.

Context is crucial

Advanced MES software dramatically improves data analytics, based on a dashboard that supports faster and better decisions that will be used to elevate production to the highest standards.

aspenONE Process Explorer, for example, means analysis is easier, faster and more effective, allowing operators; process engineers; unit managers, and executives to build a complete picture of production performance from continuous to batch.

The rich context and analytics tools help drive greater collaboration across the enterprise by enabling benchmarking and sharing of best practices for faster decision-making.

Establishing a centre of operational excellence improves communications and brings operational staff closer together.

Those chemical and petrochemical companies that adopt best practices and use the power of data visualisation software tools can better understand the story behind the data, and ensure that production outcomes meet with a profitable ending.