Electrical Equipment
Industries in the Electrical Equipment, Appliance, and Component Manufacturing subsector manufacture products that generate, distribute and use electrical power. Electric Lighting Equipment Manufacturing establishments produce electric lamp bulbs, lighting fixtures, and parts. Household Appliance Manufacturing establishments make both small and major electrical appliances and parts. Electrical Equipment Manufacturing establishments make goods, such as electric motors, generators, transformers, and switchgear apparatus. Other Electrical Equipment and Component Manufacturing establishments make devices for storing electrical power (e.g., batteries), for transmitting electricity (e.g., insulated wire), and wiring devices (e.g., electrical outlets, fuse boxes, and light switches).
Assembly Line
Behind the Scenes: GE Appliances' $80 Million Dishwasher Line
Gigaprofits: 'batteries not included'
The majority of cell manufacturers have a net profit margin in the 2-3% range. Pureplay gigafactories CATL, EVE, and Samsung SDI have higher margins in the 8-10% region. Companies tend to trade profit margins for revenue on an individual basis, (for example Sunwoda, BYD, Gotion), perhaps reflecting the price competitiveness between these large high-tier cell producers.
Dynamic state and parameter estimation in multi-machine power systems—Experimental demonstration using real-world PMU-measurements
Dynamic state and parameter estimation (DSE) plays a key role for reliably monitoring and operating future, power-electronics-dominated power systems. While DSE is a very active research field, experimental applications of proposed algorithms to real-world systems remain scarce. This motivates the present paper, in which we demonstrate the effectiveness of a DSE algorithm previously presented by parts of the authors with real-world data collected by a Phasor Measurement Unit (PMU) at a substation close to a power plant within the extra-high voltage grid of Germany. To this end, at first we derive a suitable mapping of the real-world PMU-measurements recorded at a substation close to the power plant to the terminal bus of the power plants’ synchronous generator. This mapping considers the high-voltage transmission line, the tap-changing transformer and the auxiliary system of the power plant. Next, we introduce several practically motivated extensions to the estimation algorithm, which significantly improve its practical performance with real-world measurements. Finally, we successfully validate the algorithm experimentally in an auto- as well as a cross-validation.
DMEGC Lithium-ion Battery Cell Production
Inside Schneider Electric’s Smart Factory
According to Clayton, the goal of Schneider Electric’s IIoT initiative in Lexington is to boost efficiency and overall market competitiveness by introducing technologies that modernize and reinvent the control, monitoring and management processes of the plant.
It’s part of Schneider Electric’s global effort to digitally transform its factories and distribution centers. The 183-year-old company’s supply chain encompasses nearly 300 factories and logistics centers in more than 40 countries. Most of those facilities use the same IIoT technology that the company offers to its customers.
“These facilities are core to [our] Tailored Sustainable Connected Supply Chain 4.0 program, which creates a customized, sustainable and end-to-end connected supply chain across the plan, procurement, make, customer and sustain domains,” explains Clayton.
AI tool locates and classifies defects in wind turbine blades
Using image enhancement, augmentation methods and the Mask R-CNN deep learning algorithm, the system analyses images, highlights defect areas and labels them.
After developing the system, the researchers tested it by inputting 223 new images. The proposed tool is said to have achieved around 85 per cent test accuracy for the task of recognising and classifying wind turbine blade defects.
Smart Factory in Actual Practice – Toward Autonomous Production
In Sick’s sensor factory in Freiburg-Hochdorf, driverless transport systems curve around automated production modules and workstations operated by people or collaborating human-robot teams. “The modules are cells in which the robot performs a defined task in a fixed working environment, such as the final assembly of various sensor components,” Joachim Schultis explained, Head of Operations for Photoelectric Sensors & Fibers at Sick AG “The modules are completely setup-free; format and material changes are carried out by the control system operating in the background.”
GE to advance competitiveness of wind energy with 3D printed turbine blades
The project will initially produce a full-size 3D printed blade tip for structural testing, in addition to three blade tips to be installed on a wind turbine, with the hope of reducing manufacturing cost and increasing supply chain flexibility for the components.
“We are excited to partner with the DoE Advanced Manufacturing Office, as well as with our world class partners to produce a highly innovative advanced manufacturing and additive process to completely revolutionize the state of the art of wind blade manufacturing,” said Matteo Bellucci, GE Renewable Energy’s Advanced Manufacturing Leader.