Keeping the plant operating is critical, of course, but there are many facets, many benefits to reliability that
might not be obvious to everyone. We chatted with Robert Golightly, senior manager of AspenTech’s asset-performance management, to share his perspective. Take a look…
Smart Industry: How are advancements in IIoT leading to increased sustainability?
Robert: Using data and analytics to improve decision-making is not new for asset-intensive organizations. What is new is how the IIoT can drive business sustainability by improving operational excellence with asset optimization. This is a business-sustainability story across all pillars of operational excellence: profitability, efficiency, environmental health and safety (EH&S) and workforce.
Winners will be the ones who take advantage of technology convergence in three areas:
- Real-time data
- Advanced analytics enabled by machine learning
- Rich process knowledge to drive data-driven decision-making where it matters most, whether that is improving safety, reducing energy use, bridging the talent gap or shoring up margins for commodity manufacturing and processing
Mature IIoT deployments produce higher levels of operational excellence that grow market share and increase shareholder value.
Smart Industry: How are technological advancements helping companies create more sustainable environments while reducing energy output?
Robert: From a business-sustainability point of view, all producers are looking to reduce the key manufacturing costs of feedstock, energy and maintenance, while simultaneously increasing capacity utilization and uptime to enable market-share growth and enhanced profitability throughout the commodity cycle.
Up to 40-60% of a refinery’s operating expenses are energy costs: If 10-20% of those can be eliminated through operational excellence, the result is less energy expended and lower energy costs. The IIoT enables better decision-making because it identifies more operational-excellence-improvement opportunities and offers up more information about how to save energy, etc.
It is all about the data–a typical AspenTech pilot analyzes 22 million sensor values and 135 million process data points–and all about the speed of analysis.
Energy savings within the plant fence is one thing, but there are broader sustainability implications. Think of the impact of reducing maintenance costs and increasing efficiency on emerging energy sectors like wind farms’ turbines, which are costly to fix and shut down the business when they break. Many alternative-energy providers need an easily accessible, affordable “application-ized” IIoT infrastructure for business sustainability, and in turn they can use advanced technology to develop additional new energy resources.
Smart Industry: And the safety component?
Robert: With an analytics-driven approach to asset-reliability, companies can understand and eliminate the root cause of asset failures. By “creating a world that doesn’t break down” with technology that gives early, accurate warnings of impending equipment failures and prescribes detailed corrective actions to mitigate/avoid problems, processes and equipment become less dangerous.
However, unless an IIoT solution fits in with a company’s skillsets and work processes, then it cannot successfully create safer workplaces. For IIoT to make plants, people and processes safer, technology like machine learning needs to be low-touch and “abstracted” so that maintenance and operations people can easily use it to solve problems.
Technology that works in industrial environments needs to be automated to provide the actionable information to resolve the impending breakdown with minimum disruption, and/or advises the immediate changes in operational procedures; what to do to correct the issue and eliminate the breakdown so safety issues don’t come up at all.
Smart Industry: And what about side benefits of reliability?
Robert: Achieving greater reliability with IIoT-enabled APM solutions will help solve one of the most pressing problems facing industry today: the skills shortage, talent gap, great shift change, however it is termed. Within oil and related sectors, close to 20 percent of the workforce will retire over the next few years. Chemical engineers take years of domain experience with them, expertise that quite literally ran the operation in the old days. Such knowledge is not easily replicated with new employees who lack the skills and experience. Plus, layoffs in the energy industry after 2014 climbed to over 350,000 in two years. Technology that can automate knowledge work can help here.
The industry urgently needs new path forward with solutions that overcome the prevailing realities. The sustainability of the industry depends on it.
