Bottleneck Detection

Assembly Line

I3oT (Industrializable Industrial Internet of Things) Tool for Continuous Improvement in Production Line Efficiency by Means of Sub-Bottleneck Detection Method

đź“… Date:

✍️ Authors: Javier Llopis, Antonio Lacasa, Nicolás Montés

đź”– Topics: Bottleneck Detection, IIoT, I3oT

🏢 Organizations: Ford, CEU Cardinal Herrera University


The present paper shows how to develop an I3oT (Industrializable Industrial Internet of Things) tool for continuous improvement in production line efficiency by means of the sub-bottleneck detection method. There is a large amount of scientific literature related to the detection of bottlenecks in production lines. However, there is no scientific literature that develops tools to improve production lines based on the bottlenecks that go beyond rebalancing tasks. This article explores the concept of a sub-bottleneck. In order to detect sub-bottlenecks in a massive way, the use of one of the I3oT (Industrializable Industrial Internet of Things) tools developed in our previous work, the mini-terms, is proposed. These mini-terms use the existing sensors for the normal operation of the production lines to measure the sub-cycle times and use them to predict the deterioration of the machine components found in the production lines. The sub-bottleneck algorithms proposed are used in two real twin lines at the Ford manufacturing plant in Almussafes (Valencia), the (3LH) and (3RH), to show how the lines can be continuously improved by means of sub-bottleneck detection.

Read more at Machines

Debottlenecking Takes A Broader View

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đź”– Topics: Simulation, Bottleneck Detection

🏭 Vertical: Chemical

🏢 Organizations: AspenTech, Reliance Industries, Pemex


AspenTech’s strategy is to seek more innovative and lower-cost debottlenecking solutions by looking at the system in a broader way, considering whole plant operation from a process and energy point of view as opposed to addressing each bottleneck in isolation.

One such case study involves a 39,000-tonne/yr Reliance Industries’ acrylonitrile plant in India. Here, AspenTech’s modeling tool, Aspen Plus, was used to develop a steady-state model of the total plant in an effort to address a number of processing challenges. The simulation so far has spurred a 50% reduction in hydrogen cyanide emissions, a 75% decrease in effluent color and a 15% increase in acetonitrile concentration. An ongoing study at the same site also might lead to a cut in flare losses that currently are running the equivalent of about $22,500/yr.

Another project spotlighted at the conference involves cryogenic unit number one at Pemex’s Ciudad Pemex gas processing plant in Mexico. It had been operating at an efficiency of 76.72% for C2+, well below its originally designed capability of 81.94%. Once updated to reflect the plant’s current operating conditions, the Aspen Plus model pinpointed low efficiency in a heat transfer unit. Adjusting that unit gave a production improvement worth $7.6 million/yr.

Read more at Chemical Processing