CHICAGO – Lubricant and grease production plants can improve efficiency and profitability by digitalizing their operations, an industry insider said at a conference here this month.
Digitalization is the process of converting data from analog to digital format to increase the speed and amounts of data that business can utilize. One category of application is to do so to help plant managers identify production inefficiencies and even automate certain processes.
According to Pablo Garce, sales director of ABB‘s industrial automation business, digitalization has already found results in the chemicals industry: among 300 industry professionals his company surveyed in 2016, 79 percent agreed plant automation has a decisive influence on profitability. “Once a plant is automated, the management looks for opportunities to improve further, do more and do better,” he said Sept. 10 at the North American Industrial Lubricants Congress, co-organized by ICIS and the European Lubricating Grease Institute.
Companies can decide to invest in digitalization for a number of reasons. Obvious ones include improving facility speed and yield, reducing production costs and automating certain processes. Other reasons could be attracting talent into the industry and adapting to new business models.
Xerfi Global, an international market research firm, found in the chemical industry that digitalization could both reduce total costs of plant operations by 3 to 5 percent and increase total revenue by 2 to 4 percent.
“The same results can potentially be found in lubricants and grease plants,” said Garce. In one application, a facility manager could collect, store and access data, metrics and key performance indicators from their production site. Real-time data would also be available. “The objective is to constantly monitor the production,” he explained. And the goal is to reduce the time lost in production and to help facility operators to follow the operations in progress.
To start, plant operators work with data analysts to identify key performance indicators, then identify and prioritize process bottlenecks. Management then decides which bottlenecks should be fixed, taking into consideration factors such as company policy or regulatory considerations. “This is not a one-time thing,” said Garce. “It is done continuously to generate an ongoing list of bottlenecks so that processes can be optimized over time. This can also be used to highlight where more or better data is needed,” he added.
A number of metrics can be analyzed through digitalization. On a top level, as Garce describes it, there is overall equipment effectiveness, which measures how much production time is truly productive. Another metric is total effective equipment performance, which can provide insight to the true capacity of a company’s manufacturing operation.
Underlying metrics can measure things like the total time that is scheduled for operation, uptime, the speed at which operations run and first pass yield, which represents the number of good units produced out of all units started.
Collecting and understanding these metrics can cut down on production losses. Equipment failures, idling, equipment adjustments, reduced speeds, process defects and reduced yields are all major efficiency losses that can slash into total production. While these losses cant be entirely eliminated from a facility’s work flow, their impact can be lessened.
But it’s not enough to simply install these systems. Gathering and analyzing data isn’t enough on its own. Garce said management must understand the relationships and interdependencies between the facility’s systems. “Management must also invest in training to ensure operators can effectively use the new technology,” he said.