Chip Agony Bottlenecks Automotive Leader Toyota
The semiconductor shortage in the automotive sector finally hits the leader, Toyota. According to the BBC and Wall Street Journal they plan to cut production by 40% in September. Toyota largely avoided any hits to production due to holding a larger safety stock of critical chips as compared to their competitors. The most recent supply constraint is due to disruptions in Southeast Asia with COVID-19 outbreaks.
Global automakers continue to struggle to meet automotive demand and see no end in sight to the chip shortage. Chinese automaker, Geely, claims to have been stockpiling chips since last September although they also had sluggish sales growth due to supply constraints. Others have started to seek supplier relationship management and data transparency tools to improve the likelihood of procuring future supply. Ultimately, this supply bottleneck will change management philosophies and the level of risk management is willing to accept for critical supplies.
Visual Inspection
Driven Track System Used in Auto Assembly Handling
Don’t miss a time lapse of Fastems multi-level system deployment at Sähkö-Rantek.
Acoustic Monitoring
Assembly Line
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.
2021 IW Best Plants Winner: IPG Tremonton Wraps Up a Repeat IW Best Plants Win
“If you wrapped it and just wound it straight, it would look like a record, with peaks and valleys,” says Richardson. So instead, the machines rotate horizontally, like two cans of pop on turntables. Initially, IPG used a gauge that indicated whether the film was too thick or too thin. “That was OK,” says Richardson, “but it didn’t get us the information we needed.”
Working with an outside company, IPG Tremonton upgraded the gauge to one that could quantify the thickness of the cut plastic in real time as the machine operates.
The benefits of the tinkering were twofold. First, the upgrade gave operators the ability to correct deviations on the fly. Second, “we found that we had some variations between a couple of our machines,” Richardson says. Using the new gauge on both machines revealed that one of them was producing film “a few percentage points thicker” than its twin. “We [were] basically giving away free product,” Richardson recalled. The new sensor gave IPG the information it needed to label film more accurately.
Smart conveyors streamline wet wipes packaging challenges
Wet wipe manufacturing automation can produce up to 500 stacks of wipes per minute, in counts ranging from 20 to 100 single-ply sheets per stack. At these high throughput levels, downstream systems for primary and secondary packaging like shrink wrappers and case packers cannot handle the volume of product flow unless it is split into multiple packaging machinery lines.
No matter how efficient shrink wrappers, labelers and case packers may be, if the wet wipes packaging line does not use conveyors adequately designed for the handling of fragile products like wet wipes, and precisely stage these products for infeed, the product quality, throughput speed and cost-efficiency of the entire production and packaging line will be compromised.
Big Data Analytics in Electronics Manufacturing: is MES the key to unlocking its true potential?
In a modern SMT fab, every time a stencil is loaded or a squeegee makes a pass, data is generated. Every time a nozzle picks and places a component, data is generated. Every time a camera records a component or board inspection image, data is generated. The abundance of data in the electronics industry is a result of the long-existing and widespread process automation and proliferation of sensors, gauges, meters and cameras, which capture process metrics, equipment data and quality data.
In SMT and electronics the main challenge isn’t the availability of data, rather the ability to look at the data generated from the process as a whole, making sense of data pertaining to each shop floor transaction, then being able to use this data to generate information from a single point of truth instead of disparate unconnected point solutions and use the generated insight to make decisions which ultimately improve process KPIs, OEE, productivity, yield, compliance and quality.
Energy Harvesting Startups Could Power Some IoT Dreams
Removing batteries from the industrial equation cuts costs and reduces the hours that people spend replacing them. Using batteryless equipment in industrial and consumer settings could also greatly reduce the number of batteries that are thrown into landfills around the globe. It is estimated that 3 billion batteries a year are discarded in the U.S. alone!
For instance, Everactive argues that if you were to deploy 10,000 battery-powered industrial IoT sensors across your facility to transmit real-time data about the health of your machinery, over time your team would be replacing around 2,000 batteries a year. Many of these sensors would be located in difficult-to-reach areas, further increasing the time and expense needed to replace the chemical cells.
Aerospace, Defense and Industry 4.0
“Designing for manufacturability, modeling the production environment, and then producing our products with a minimum of duplicated effort—this can give us the breakthroughs in speed and affordability that the A&D environment needs in a time of limited budgets and rapidly changing threats,” explains Daughters. “These technologies are an essential component to our ‘digital thread’ across the product life cycle. They give us the ability to simulate tradeoffs between capability, manufacturability, complexity, materials and cost before transitioning to the physical world.”
“In a nutshell, I4.0 involves leveraging technology to better serve the world,” says Matt Medley, industry director for A&D manufacturing at IFS, a multinational enterprise software company. “More than just collecting and processing mounds of data via sensors and the Industrial Internet of Things (IIoT), I4.0 is turning data into actionable intelligence to not only drive efficiency and grow profits, but to also help companies be good stewards of our natural resources and local communities. Aerospace and defense companies whose enterprise software can keep pace with developments like additive manufacturing, AI, digital twins, and virtual and augmented reality (V/AR) are the ones that will thrive in an increasingly digital 4.0 era.”
Concept Prove-Outs Prove Their Worth in Robotic Finishing
During shop visits, Modern Machine Shop editors have gotten used to seeing rows of people huddled over benches with spotlights, scopes and hand tools. In fact, the sight is so common that the odd juxtaposition of tedious manual work and sophisticated, automated CNC machining processes can be easy to overlook.
Different automated material removal applications teach similar lessons about the value of early testing, close collaboration and adventurous thinking.
Industry 4.0 and the Automotive Industry
“It takes about 30 hours to manufacture a vehicle. During that time, each car generates massive amounts of data,” points out Robert Engelhorn, director of the Munich plant. “With the help of artificial intelligence and smart data analytics, we can use this data to manage and analyze our production intelligently. AI is helping us to streamline our manufacturing even further and ensure premium quality for every customer. It also saves our employees from having to do monotonous, repetitive tasks.”
One part of the plant that is already seeing benefits from AI is the press shop, which turns more than 30,000 sheet metal blanks a day into body parts for vehicles. Each blank is given a laser code at the start of production so the body part can be clearly identified throughout the manufacturing process. This code is picked up by BMW’s iQ Press system, which records material and process parameters, such as the thickness of the metal and oil layer, and the temperature and speed of the presses. These parameters are related to the quality of the parts produced.