Blake Griffin
Articles
Short- and long-term impact of low-voltage ac motor market deceleration
The low-voltage ac motor market is expected to decline in 2024 after posting years of double-digit growth because of the COVID-19 pandemic.
Ultra low-voltage motor and drive architectures are gaining traction
The ultra low-voltage (ULV) market is gaining traction due to safety and installation concerns and the rise of AMRs and AGVs.
Acquisitions reveal motor supplier strategies
The top three suppliers of low voltage ac motors made waves in the motor and drives space with a string of acquisition announcements in early August. First, WEG announced its acquisition of Gefran’s motion control business.
The electric steel dilemma and its impact on motor vendors
Because of the increased demand for electric steel, it is difficult for vendors to acquire the necessary goods to complete their productions.
Data centers at the front line of future motor technology
Data centers are becoming more powerful as they gather more data and need high-efficiency motors to match their data consumption, which takes a lot of energy.
World events create disruptions in motors and drives
There are several factors in crucial areas of the motor and drive supply chain to note as the Russian invasion of Ukraine continues. See video.
Trends in the LV drives market
Market research shows three trends influencing the drives market: functional safety, predictive maintenance and efficiency regulations.
Low-voltage drive market projected to have slow, steady recovery
Labor shortages and supply chain disruptions are all coming together to cause a much slower recovery in the low-voltage drive market according to a report by Interact Analysis.
Infrastructure bill projected to grow low-voltage market in key areas
The low-voltage (LV) drives market, like all other markets, dealt with a turbulent 2020 brought on by the COVID-19 pandemic, but it should rebound if the Infrastructure Bill passes.
Predictive maintenance value: Smart sensors, machine learning, new industrial business models
Smart sensors and machine learning algorithms detect anomalies in industrial machines, and as algorithms become better trained, software can accurately predict when machines with industrial automation is at risk of failure. New business models for machine as a service (MaaS) may help overcome slow adoption of predictive maintenance technologies.