Cultivating Manufacturing Sustainability with Technology

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Assembly Line

Toward smart production: Machine intelligence in business operations

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✍️ Authors: Duane S. Boning, Vijay D'Silva, Pete Kimball, Bruce Lawler, Retsef Levi, Ingrid Millan

πŸ”– Topics: Manufacturing Analytics, Machine Intelligence

🏒 Organizations: McKinsey, Vistra, MIT


Our research looked at five different ways that companies are using data and analytics to improve the speed, agility, and performance of operational decision making. This evolution of digital maturity begins with simple tools, such as dashboards to aid human decision making, and ends with true MI, machines that can adjust their own performance autonomously based on historical and real-time data.

Read more at McKinsey Insights

Consulting 4.0: Looking beyond People and Process, into Technology and Business Sustainability

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✍️ Author: Rui Gonçalves

🏒 Organizations: Magellan Consulting


Traditional consulting, however, is broken, in the sense that most consulting companies focus on people and processes, primarily considering technology as merely a tool to achieve set deliverables. This lack of clarity hurts businesses. Technology companies on the other hand focus on the installation of their tech, rarely ever focusing on its management and acceptance, especially indirect interactions, which leads to user frustration and less than optimal value derivation. Ideally, Industry 4.0 needs consulting that looks beyond people and process, into technology and business sustainability.

Read more at Critical Manufacturing

Industry 4.0 and the pursuit of resiliency

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✍️ Author: Kate Carroll de Gutes

πŸ”– Topics: Zero Defect Manufacturing, Visual Inspection, Asset Performance Management

🏒 Organizations: IBM


There are two parts to the Zero D story. Visual inspection and asset performance management (APM). Visual inspection uses computer vision models focused on quality inspection. APM uses machine learning models based on time series data to determine health of assets and probable failures in the future. Toyota is using Maximo Visual Inspection, and now they are also using the Maximo Asset Performance Management (APM) suite. They tested Maximo APM on some of their machinery that does liquid cooling and found that was another problem area for them. By implementing the software into this pilot, they are now able to monitor the asset health 24Γ—7 and predict probability of failure in the future.

Read more at IBM Blog

Radford uses 3D printing to customize automotive manufacturing

The Full Potential of a Military Metaverse

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✍️ Authors: Jennifer Mcardle, Caitlin Dohrman

πŸ”– Topics: Metaverse

🏭 Vertical: Defense


A defense metaverse could build on this digital education ecosystem but it would be far more immersive, providing opportunities to draw on some of the mixed-reality advancements in education that are already taking place in the civilian and military worlds. Additionally, a defense metaverse offers the possibility of connecting virtual environments for acquisitions with those used for experimentation or training, allowing acquisitions professionals to quickly test or assess their designs in a virtual world that mimics the future operating environment β€” all while providing a modicum of operational security that the live environment may not afford. Lastly, a defense metaverse β€” much like many platforms β€” should also facilitate technology reusability, helping to drive down costs associated with acquisitions.

Read more at War on the Rocks

Evaluation Criteria for Trajectories of Robotic Arms

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πŸ”– Topics: Robotic Arm

🏒 Organizations: Slovak University of Technology, Photoneo


This paper presents a complex trajectory evaluation framework with a high potential for use in many industrial applications. The framework focuses on the evaluation of robotic arm trajectories containing only robot states defined in joint space without any time parametrization (velocities or accelerations). The solution presented in this article consists of multiple criteria, mainly based on well-known trajectory metrics. These were slightly modified to allow their application to this type of trajectory. Our framework provides the methodology on how to accurately compare paths generated by randomized-based path planners, with respect to the numerous industrial optimization criteria. Therefore, the selection of the optimal path planner or its configuration for specific applications is much easier. The designed criteria were thoroughly experimentally evaluated using a real industrial robot. The results of these experiments confirmed the correlation between the predicted robot behavior and the behavior of the robot during the trajectory execution.

Read more at MDPI

Robust Routing Using Electrical Flows

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✍️ Authors: Ali Kemal Sinop, Kostas Kollias

🏒 Organizations: Google


We view the road network as a graph, where intersections are nodes and roads are edges. Our method then models the graph as an electrical circuit by replacing the edges with resistors, whose resistances equal the road traversal time, and then connecting a battery to the origin and destination, which results in electrical current between those two points. In this analogy, the resistance models how time-consuming it is to traverse a segment. In this sense, long and congested segments have high resistances.

Read more at Google AI Blog

Improving PPA In Complex Designs With AI

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✍️ Author: John Koon

πŸ”– Topics: Reinforcement Learning, Generative Design

🏭 Vertical: Semiconductor

🏒 Organizations: Google, Cadence, Synopsys


The goal of chip design always has been to optimize power, performance, and area (PPA), but results can vary greatly even with the best tools and highly experienced engineering teams. AI works best in design when the problem is clearly defined in a way that AI can understand. So an IC designer must first see if there is a problem that can be tied to a system’s ability to adapt to, learn, and generalize knowledge/rules, and then apply these knowledge/rules to an unfamiliar scenario.

Read more at Semiconductor Engineering

Surge Demand

Manufacturing technology orders grew by 55% to nearly $6 Billion in 2021. Yokogowa releases their industrial autonomy and sustainability survey while IBM bets on it as a business strategy. AutoDesk is building their portfolio for the digital factory technologies through acquisitions. BioNTech creates mobile vaccine factories.