OM in the News – The OM Blog by Heizer, Render, & Munson

OM in the News: Understanding Manufacturing AI Terminology

Walk into almost any operations and supply chain meeting today and you’ll hear it:

“We should use AI for this.”
“Can we plug in an LLM?”
“Let’s add a copilot.”

Thanks to Industry Week (April 13, 2026) here is a guide to the AI vocabulary showing up in manufacturing and supply chain environments.

Machine Learning Machine learning uses historical data to detect patterns, improve predictions and support decisions. In real-world operations, that includes:

Demand forecasting
Inventory optimization
Predictive maintenance
Quality and anomaly detection

LLM (Large Language Model) LLM refers to systems that can read and generate human-like text. It processes and generates language based on patterns learned from large datasets. It shows up:

Summarizing supplier emails or RFQs
Drafting customer responses
Translating ERP data into plain language

LLMs don’t “know” a business unless connected to the firm’s data. Without that context, they can sound confident—but be wrong.

Copilots “Copilot” is one of the most overused—and misunderstood—terms. They are a layer that sits on top of a business system (ERP, CRM, email) to assist users in real time. It is useful for:

Suggesting responses inside email
Helping navigate ERP workflows
Recommending next steps

A copilot doesn’t replace a system—it improves how people interact with it.

Agents Agents move from assisting to acting. They are systems that can take a goal and execute steps to achieve it.

Examples:

Monitoring inventory
Detecting shortages
Reaching out to suppliers
Proposing or initiating reorders

Most agent-based systems are still early. They require strong guardrails and tight integration to work reliably in production environments.

Embeddings (The Quiet Connectors) Embeddings convert a company’s data into a format AI systems can understand and search. That’s what allows AI to:

Reference ERP data
Search internal documents
Provide context-aware responses

For operations students and faculty, the goal is not to become AI experts. It’s to understand the language well enough to ask better questions and identify where these tools can create real advantage.

OM in the News: Running a Factory on Recycled EV Batteries

Electric-vehicle startup Rivian has found an unusual power source for its Illinois car factory: old batteries from its own cars. Rivian is reusing EV batteries for energy storage—the largest repurposed-battery energy storage system for an automotive manufacturer in the U.S., says The Wall Street Journal (April 14, 2026).

Rivian’s operation will be the largest repurposed-battery energy storage system for an auto manufacturer in the U.S

Once completed later this year, Rivian’s plant in Normal, Ill., will draw electricity from more than 100 Rivian EV batteries in an area the size of a small parking lot. It will reduce Rivian’s dependence on the power grid during peak demand hours. It saves Rivian money on what it takes to run the plant.

“It reduces the demand on the grid, which is great. These batteries are already built,” said Rivian’s CEO. “We need to integrate them and connect them together, but that can happen quite fast. They don’t have to get imported from some other place.”

This is the latest example of the battery-energy storage industry boom in the U.S., where lithium-ion packs—not dissimilar to those in EVs—are increasingly used to power businesses, industrial facilities, residential zones and artificial-intelligence data centers.

The AI boom is part of what’s driving unprecedented energy demand in the U.S. Electricity prices around the country are rising so quickly that they are outpacing inflation, rising 4.5% between 2024 and 2025.

Many automakers, including Ford and GM, are retooling battery factories once meant for EVs to meet that demand, rather than let those facilities sit idle. Meanwhile, energy storage was the fastest-growing business last year for Tesla, which has long supplied batteries for residential and commercial power. The setup is expected to initially provide 10 megawatt-hours of energy, equivalent to about 1,000 home-energy battery storage units linked together.

Classroom discussion questions:

What are the advantages and disadvantages of Rivian’s approach?
How do other firms handle the energy demands from the AI boom?

OM in the News: UPS Turns to RFID

United Parcel Service is rolling out technology to more closely track the billions of small packages that move through its U.S. network each year, reports The Wall Street Journal (April 15, 2026).

UPS has invested $100 million to date to set up RFID technology across its network

The company said the change will increase visibility throughout its small-package delivery network, while increasing delivery accuracy and reducing the manual labor needed to scan individual parcels.

“What this does is it offers our customers real-time, near real-time, visibility of where their packages are at within our network,” said a UPS exec.

The capability is a step beyond the shipment-tracking information widely used today, which relies on workers scanning bar codes as packages enter and leave warehouses or vehicles. That tracking point typically lags behind a package’s current location, leaving gaps in visibility where packages may be misplaced or lost.

UPS is now embedding RFID tags into shipping labels and has installed RFID sensors on all its U.S. delivery trucks, at its more than 5,500 retail stores and in its final-mile delivery centers.

The technology allows UPS to automatically sense and track when a package crosses a threshold into or out of a building or vehicle. That will give customers a more up-to-date, accurate picture of where packages are, though it does not include real-time location tracking.

The company in part uses the technology to identify what it calls misloads, where packages are loaded onto the incorrect delivery truck. The RFID tag on a given package sets off a sensor as it’s loaded into a delivery truck and makes a noise indicating if the package is on the wrong vehicle.

UPS said misloads have dropped near 70% since it started using the technology in 2024, and that the RFID technology will eliminate about 20 million manual scans per day.

The high cost of individual tracking devices and the complexity of small-package delivery networks have limited tracking technology to more industrial applications as well as shipping high-value goods such as healthcare products, electronics and luxury items. UPS said the cost of RFID tags has come down to a few cents each, allowing the company to deploy the technology at scale.

Classroom discussion questions:

What are the advantages and disadvantages of RFID?
Why are misloads to be avoided?

OM in the News: Delta’s Vertical Integration Risk Pays Off

Vertical integration is an interesting topic in Chapter 11 of your Heizer/Render/Munson text. There are plusses and minuses, and we warn: “Most organizations are better served by concentrating on their own specialty and leveraging suppliers’ contributions.”

But Delta Air Lines, facing billions of dollars of pain at the fuel pump (because of Iran’s blockage of the Straits of Hormuz) along with all the other carriers, is unique. It happens to own its own gas station, writes The Wall Street Journal (April 10, 2026).

Jet-fuel prices have roughly doubled since late February, pushing up airlines’ costs.

Since 2012, Delta has been the owner of a Pennsylvania refinery that processes crude into fuel. Over the years, the investment has looked like either a stroke of genius or a boondoggle, generally depending on the price of oil. Since the U.S. and Israel began carrying out strikes on Iran, the refinery is set to pay off again for Delta. With it, Delta has an asset that can help it offset some of the recent surge in fuel prices.

Energy experts rolled their eyes when Delta plunked down $150 million for the refinery. If the plant was such a good investment, why was ConocoPhillips, its previous owner, shutting it down? Rival airline executives scoffed that they would benefit from increased jet-fuel output on the East Coast without the headaches of refinery ownership.

Now even United, one of Delta’s top rivals, has acknowledged that the refinery benefits Delta. Its CEO Scott Kirby states: “Right now the crack spread (the gap between the price of jet fuel and the price of crude oil) is much higher…and so they’ll get real benefit from the higher crack spread that will be unique to them.”

Delta has said that the refinery makes an operating profit most years. The airline has said owning the refinery insulates it from supply disruptions in the Northeast and helps mitigate risk from volatile prices—effectively lowering its jet-fuel costs, often by several cents a gallon. In 2022, when fuel prices surged after Russia began its invasion of Ukraine, the refinery helped it save $785 million.

But the airline has had to pour money into the plant, which is more than a century old, to keep it running smoothly, investing $1.6 billion in capital expenditures over the years.

Classroom discussion questions:

Did the purchase make sense for Delta?
Many economists think the refinery was a costly mistake. Why?

OM in the News: Weight-Loss Drugs Crush Food Demand as Farmers Face Dumping Mountains of Potatoes

The rising popularity of weight-loss drugs like Ozempic, Wegovy, and Zepbound (GLP-1 agonists) is significantly impacting the food industry, resulting in reduced food demand, changes in consumer purchasing habits, and potential surpluses for agricultural producers, according to Fox News (April 1, 2026).

Impact on Food Demand and Consumption

Reduced Overall Demand: Users of weight-loss drugs often eat less and report a decreased appetite, with some users consuming up to 50% less than before taking the medications.
Andy Goodacre has about 1.3 million pounds of top-quality potatoes at risk of going to waste because of changing diet habits

Surplus Agricultural Products: Farmers, particularly in the United Kingdom, are facing challenges with rising surpluses of traditional staples, such as potatoes, as consumer demand declines.
Shifting Restaurant Trends: Restaurant owners report that customers are ordering fewer items, selecting lighter options, and often not finishing their meals, leading to a decline in overall food sales at restaurants.
Impact on Packaged Goods: Food companies, including snack manufacturers, are evaluating the long-term impacts of these drugs on consumer purchasing behavior for high-sugar or less-healthy items.

Changes in Eating Habits and Nutrition

Reduced “Food Noise”: Users report decreased cravings for alcohol, salty snacks, and high-fat foods, which is reshaping American tastes and reducing demand for ultra-processed foods.
Focus on Healthier Options: Many users are pivoting towards healthier, lower-calorie options, and in some cases, increasing their intake of protein to combat muscle loss.
Concerns About Malnutrition: Some researchers are flagging potential risks of malnutrition and micronutrient deficiencies, as reduced food intake can limit the intake of necessary nutrients.

Future Projections

Long-Term Industry Shift: By 2035, it is projected that 9% of the U.S. population may be on weight-loss drugs, which could lead to a sustained, significant reduction in the consumption of soft drinks, alcohol, and snacks.
Adapting the Food Sector: The food industry is beginning to adapt by considering adjustments in portion sizes and developing products that align with the dietary needs of GLP-1 users.

Classroom discussion questions:
1. What forecasting approaches do the farmers and restaurants need to consider?
2. How should a firm like Frito-Lay address this issue?

OM in the News: America Now Has an EV Rust Belt

At first, North America’s biggest auto-parts supplier was thrilled to snag the job of making enclosures for the batteries in GM’ new electric pickup. The contract was so big—and promised to be for years to come—that Magna International built a new $575 million factory in a Michigan cornfield. And Michigan even offered a $44 million incentive package to draw the promise of new jobs–a topic in Chapter 8.

Five years later, that million-square-foot plant is mostly empty and losing money, a casualty of America’s messy breakup with EVs, reports The Wall Street Journal (April 1, 2026). It is one of dozens of now desolate EV parts plants across the country. It can take years to pivot a factory and supply chain from one type of vehicle to another. And it would take 4-6 months of higher gas prices for most Americans to reconsider more fuel-efficient vehicles– an unlikely prospect. Detroit automakers have scrapped their boldest EV dreams—and are looking beyond $50 billion in charges tied to broken supplier contracts and wasted investments.

The deserted Magna factory in St. Clair was expected to stay busy for years.

Magna, which has more than 300 factories around the globe and parts in nearly every car on the road today, has been left holding the keys to the St. Clair, Michigan building that is bigger than 20 football fields. The Canadian company needs to find a second life for the factory and the hulking rows of assembly-line robots. A few years ago, Magna had plans to build an entirely new business unit around EV battery enclosures.

The EV slide is reverberating through the automotive industry’s sprawling supply chain. Multinational companies such as Magna, Dana and BorgWarner slashed jobs and closed plants due to the EV pullback, while a string of smaller manufacturers shut down altogether. Last year, more than $20 billion in previously announced investments in EV and battery facilities were wiped out.

Smaller suppliers have little recourse to recoup costs when automakers cancel a vehicle program and stop buying parts. They typically absorb the upfront cost of setting up an assembly line with the expectation of recouping it over time as parts are shipped. GM’s supplier contracts were struck with the expectation that GM would be building one million EVs a year. By December, 2025 the company was selling around 8,000 a month.

Classroom discussion questions:

Discuss the typical incentives offered to attract a new plant.
Why has the EV trucking business been especially hard hit?

OM in the News: AI’s Big Manufacturing Productivity Gains

The efficiency and productivity improvements AI can deliver through automation and digitalization will help bridge manufacturing’s workforce gap, writes Industry Week (March 13, 2026).

Similar to the PC revolution decades ago, all signs point to AI following suit with enhanced productivity and profitability. Productivity soared when PCs became interconnected across organizations. Manufacturing will see the same breakthrough with “embedded AI”—to help ease workforce bottlenecks with specific solutions. On the shop floor, for example, predictive-maintenance AI (see Chapter 17) can analyze sensor data to forecast equipment failures and avoid labor-sapping downtime.

AI vision systems (Chapter 7) can catch defects on production lines at a pace beyond human capabilities and without the repetition-induced fatigue and employee turnover. Collaborative robots (cobots) and automated mobile robots transport material and can assist with assembly and repetitive operations. AI’s coding capabilities extend to numerical control and other industrial equipment, speeding up setup time and productivity in hard-to-fill technical positions.

The interaction of embedded AI, agent-based AI, and machine learning across different areas of an organization holds the greatest promise in solving long-term labor shortages. AI can already let a customer snap a photo of a damaged part and identify it for replacement. Its real power will manifest when AI can also determine the part’s inventory status and locations, establish shipping terms and timing, add the part to the procurement queue to replenish once it’s sold, alert engineering that a design change for a chronic defect may be in order, and propose alternative designs.

Here is a current example involving AI across systems: the big semiconductor company AMD is using generative AI to track down the root cause of delivery delays, simplifying complex supply chain interactions to transform a complex, specialist-dependent, labor-intensive manual process into faster issue resolution and better decision-making. The system cuts the time needed for what was a 14-step process taking 20-30 minutes by 90%, saving more than 3,100 staff hours a year.

Also coming soon to these intelligent product recommendation engines is an ability to parse what can be 50-page tender documents to extract multiple configurable products for sales quotes. That not only saves time, but also enables junior staff to handle work that has previously required experienced hands.

Classroom discussion questions:

What can AI do to improve a procurement system?
What does “embedded AI” mean?

OM in the News: Amazon Goes Rural

In dozens of thinly populated regions across the country, Amazon is building new delivery hubs to deliver packages in around 2 days. That might not seem especially rapid at a time when the e-commerce giant is introducing one-hour delivery in some areas, but residents of some far-flung Montana hamlets were used to waiting up to a week for their orders. It is part of a $4 billion investment by Amazon to push its signature speedy delivery further into the rural recesses of the U.S., writes The Wall Street Journal (March 22, 2026)

An Amazon driver taking a photo after dropping off a package in Connor Montana

The effort helps Amazon reduce its reliance on the U.S. Postal Service, a relationship that has become rocky following a dispute over contract terms. Amazon says it aims ultimately to have 200 rural delivery hubs serving around 13,000 ZIP Codes covering around 1.2 million square miles of America—an area the size of Texas, California and Alaska combined.

Delivering packages within Amazon’s signature 2-day frame means drivers contend with backcountry challenges such as bighorn sheep on the road, dangerously high winds in mountain passes and roads that are impassable during parts of the year.

Over the past decade, Amazon has expanded from major cities to regional urban centers by drawing ever larger circles of coverage. That is now allowing the company to lean on those urban hubs to speed up deliveries in ranch country. There are signs that Amazon customers in remote areas are just as likely to get hooked on speedy delivery as city slickers.

Amazon is experimenting with speedier delivery across its network as it competes with longtime rival Walmart and delivery upstarts such as Uber and DoorDash. In urban areas, the company has started offering 1-hour and 3-hour delivery as premium options. Amazon recently acquired a Swiss startup called Rivr, which is building 4-legged robots that could drop packages off on doorsteps. The e-commerce giant is also dipping its toe in the big-box retail business, with plans for a 230,000-square-foot megastore outside Chicago.

Classroom discussion questions:

What are the complications in trying to serve remote locations with 2-day delivery?
Why does the firm think the extra expenses will pay off?

OM in the News: Six Jobs From the 1950s That Barely Exist Today

The U.S. workforce has transformed dramatically since the 1950s, a decade marked by economic prosperity, suburban expansion, and rapid industrialization, writes History Facts. Some careers that may have seemed stable and essential then, but time, technology, and changing needs have made them and many others all but disappear. Here are 6 jobs that were popular in the 1950s but are now nearly extinct.

Telephone Switchboard Operator. Before direct-dial telephone systems took over, switchboard operators were the backbone of communication, ensuring calls reached the right destination. In the 1950s, the U.S. had about 1,342,000 telephone switchboard operators. It was a demanding job that required quick reflexes. By the 1970s, automated dialing systems phased out the need for human operators.

Milkman. Having fresh milk delivered to your doorstep was once a common part of American life. The local milkman made rounds, leaving glass bottles on doorsteps and retrieving empty ones. This service was necessary before the widespread adoption of home refrigeration. By 2005, this number had dwindled from over 50% of homes receiving delivery to just 0.4%.

Elevator Operator. In the mid-20th century, elevator operators were essential for manually controlling elevators in department stores, office buildings, and hotels. At its peak, the profession employed more than 90,000 workers. Only a few historic buildings still employ operators today, for nostalgia.

Typist. Secretarial jobs became essential during the Industrial Revolution, as businesses generated more paperwork than ever before. By 1950, secretarial work had become the most common occupation for women, with 1.7 million employed. While secretarial roles still exist today, the number of workers specifically categorized as “word processors and typists” has declined to 37,200.

Motion Picture Projectionist. Projectionists played a vital role in the moviegoing experience in the 1950s, operating and maintaining film projectors in theaters. By 2013, 92% of movie theaters had made the switch to digital projection. In 1950, 26,000 people were employed as projectionists. By 2023, that number had fallen to 2,610.

Gas Station Attendant. Full-service gas stations were the standard in the 1950s, with attendants pumping gas, checking oil levels, cleaning windshields, and inspecting tire pressure. The 1973 oil crisis, which led to soaring gas prices, accelerated the transition to self-service as both businesses and consumers sought cost-saving measures. (Today, New Jersey is the only state that prohibits drivers from pumping their own gas).

Classroom discussion questions:

What jobs that exist today do you think will be extinct in 20 years?
What new jobs have been created in this past 1/2 century?

OM in the News: FedEx Is Planning an AI Agent Workforce

FedEx is building out an army of AI agents to work alongside its human workforce, positioning itself to tap the latest wave of technology crashing through corporate America, reports The Wall Street Journal (March 13, 2026).

The shipping giant, which already deploys artificial intelligence in software development and other areas, is now looking to drive AI agents further into operations, including network planning and business processes. By 2028, FedEx expects to have AI integrated into more than half of its core operational workflows. FedEx is currently focused on setting up the underlying data and management foundation to oversee its AI bots.

Though logistics providers like FedEx are aiming to adopt AI, they’re grappling with challenges like managing numerous, disconnected data sources. “Logistics can be very fragmented—especially if you think of a global organization with their network being everywhere, it makes it difficult to standardize,” said an industry consultant.

As its underlying tech is completed, FedEx expects to roll out AI and AI agents that connect macro and microeconomic trends to better plan its network. In marketing and campaign management, FedEx will create a hierarchy in which there’s a “manager agent,” an “audit agent” and a “worker agent.” The goal of the hierarchy is to ensure that the agents have a trail of accountability for their actions.

At the moment, FedEx’s enterprise data platform, called Atlas, supports more than 200 AI use cases across the supply chain, commercial teams and enterprise functions. It has already turned on AI agents in areas such as software development, where they are developing and testing code. In operations, agents are helping customers clear customs more quickly.

Plans for FedEx’s AI agents also involve getting its humans ready to interact with the technology. the company just launched an AI education program for 300,000 of its employees, as well as a more advanced version for its technology workers. Each employee received a customized training depending on their role. FedEx says it doesn’t plan for those agents to replace its workers.

Classroom discussion questions:

Why is FedEx pushing for more AI agents?
How will agents be used in operations?

OM in the News: The Robotics Supply Chain

The next 20 years are not just about making robots better, but also about how they will be used in all sorts of industries, from small tests to big factories. The real challenge is having specialized engineering skills, great manufacturing, and dominating software, reports Industry Week (March 11, 2026).

There are 6 key areas that make all the difference in this industry. Here is a breakdown of the cost of the parts that go into a robot:

1. Actuators & Gearboxes (35-40%): The physical muscle.

2. Robot Structure / Manipulators (15-20%): The physical frame and integration.

3. Sensors & Perception (10-15%): The eyes and ears.

4. AI Compute / Control (10-15%): The operational brain.

5. Battery / Power Systems (10-15%): The energy storage for mobile units.

6. Precision Motion Components (5-10%): The components required for fine movements.

This list shows that a robotics breakthrough isn’t just software advances; it depends on physical components and the supply chains that produce them. But there are 3 chokepoints (bottlenecks).

#1: Precision Reducers, controlled by Japan. Robots can’t move with a lot of power and precision without special parts (harmonic and cycloidal reducers). Two companies in Japan make 70% of these parts used all over the world. Spending more money won’t allow other companies to make these parts, because they need special knowledge about metals and years of experience making precise parts.

#2: AI Compute (The Intelligence Standard), controlled by the U.S. Today’s robots, especially those that use reinforcement learning, need powerful computers to work properly. NVIDIA’s CUDA system has become the leading platform used by robots that learn and think. Making a better chip is not enough if you can’t replace the software that all robotics engineers already use.

#3: Battery Supply Chain, controlled by China. Robots are changing from big, stationary machines to mobile ones. This means batteries are now a crucial part of making them work. One company in China, CATL, controls 1/3 of the world’s battery market. China has a very strong grip on this supply chain.

The global map of robotics is specialized. There is a multi-polar supply chain that is difficult to disrupt:

USA: “The “Brain.” (software, autonomy, AI compute).

Japan: The “Hardware King.” (motors, gearboxes, precision engineering).

Germany: The “Precision Engineer.” ( mechanical systems, high-end production).

China: The “Scale & Power.” (manufacturing speed, massive infrastructure, battery supremacy).

Taiwan: The “Linear Specialist.” ( The linear guides and ball screws essential for motion).

Classroom discussion questions:

Why must operations managers understand these costs and bottlenecks?
What are the supply chain implications?

OM in the News: Bringing Mac Mini Production Stateside

Apple just announced a significant expansion of its Houston manufacturing operations, confirming that production of the Mac mini will move to the U.S. for the first time as part of a broader investment in advanced manufacturing and AI infrastructure. The move will also see Apple expand AI server production at the Texas site and open a new Advanced Manufacturing Center, initiatives that together are expected to create thousands of jobs.

The decision marks a notable shift in the company’s global manufacturing strategy, writes Yahoo Finance (Feb. 28, 2026). The move follows a wider trend among technology firms seeking to diversify supply chains and expand domestic production capacity, particularly in high-value electronics manufacturing.

Alongside Mac mini production, Apple is ramping up output of advanced AI servers at the Houston site, an initiative that began in 2025. The expansion reflects Apple’s growing investment in AI infrastructure, an area that has become central to both consumer devices and cloud services.

Beyond hardware production, Apple is also investing in workforce development with the launch of an Advanced Manufacturing Center in Houston. The facility will provide hands-on training in advanced manufacturing techniques. The center will train students, supplier employees, and manufacturers in processes used in Apple’s own production lines. Apple engineers will teach how U.S. manufacturers can adopt new technologies and improve efficiency, strengthening the domestic manufacturing ecosystem while building a pipeline of skilled workers.

Apple’s expansion comes amid a broader push to localize manufacturing in North America, driven by supply-chain resilience concerns, geopolitical tensions, and government incentives. Bringing Mac mini production home signals that high-tech consumer electronics assembly—traditionally concentrated in Asia—may increasingly be split across multiple regions. Meanwhile, Apple’s investment in AI server production reflects surging demand for data-center hardware as AI applications expand.

By combining Mac mini assembly, AI server production, and advanced manufacturing training, Apple is positioning Houston as a key node in its global supply chain—while signaling a deeper commitment to U.S. manufacturing capacity. As reshoring momentum continues, Apple’s move could encourage other electronics manufacturers to consider similar strategies, particularly for high-value or strategically important products.

Classroom discussion questions:

Why is Apple reshoring this particular product?
Why is it difficult to bring manufacturing of high-tech products home?

OM in the News: The Top 10 Most Dangerous Jobs in America

Every 104 minutes, the Bureau of Labor Statistics (BLS) says an American worker loses their life on the job. While some of us might consider a bad day at work to be a crashed computer or a long class or meeting, thousands of Americans face life-or-death stakes every day they begin their jobs. From the peaks of skyscraper steel to the depths of the Pacific Northwest forests, here are the 10 most dangerous jobs in the U.S. today, according to Industrial Safety & Hygiene News (Feb, 26, 2026)

1. Logging Workers

Fatality Rate: 98.9 per 100,000 workers. Primary Cause of Death: Contact with objects/equipment (falling trees). The Hazard: Falling trees and heavy machinery

2. Fishing and Hunting Workers

Fatality Rate: 86.9 per 100,000 workers. Primary Cause of Death: Transportation incidents (drowning/capsizing). The Hazard: Drowning and vessel capsizing

3. Roofers

Fatality Rate: 51.8 per 100,000 workers. Primary Cause of Death: Falls to a lower level. The Hazard: Gravity.

4. Refuse & Recyclable Collectors

Fatality Rate: 41.4 per 100,000 workers. Primary Cause of Death: Transportation (struck-by vehicle). The Hazard: Being struck by passing motorists.

5. Aircraft Pilots & Flight Engineers

Fatality Rate: 31.3 per 100,000 workers. Primary Cause of Death: Crashes in small aircraft. The Hazard: Mechanical failure or weather in bush/regional flying

6. Construction Helpers

Fatality Rate: 27.4 per 100,000 workers. Primary Cause of Death: Falls and exposure to harmful substances. The Hazard: “The Fatal Four” (Falls, Struck-by, Caught-in, Electrocution)

7. Heavy & Tractor-Trailer Truck Drivers

Fatality Rate: 26.8 per 100,000 workers. Primary Cause of Death: Transportation incidents (roadway collisions). The Hazard: Highway collisions and fatigue

8. Grounds Maintenance Workers

Fatality Rate: 20.5 per 100,000 workers. Primary Cause of Death: Falls and landscaping equipment. The Hazard: Equipment entanglement and heat stroke

9. Agricultural Workers

Fatality Rate: 20.2 per 100,000 workers. Primary Cause of Death: Transportation and contact with machinery. The Hazard: Tractor rollovers and silo entrapment

10. Iron and Steel Workers

Fatality Rate: 19.8 per 100,000 workers. Primary Cause of Death: Falls, slips, and trips. The Hazard: Falls and swinging heavy loads.

As we see, logging is the most dangerous profession by a massive margin. Logging workers are nearly 33 times more likely to die on the job than the average worker. The national average across all jobs is 3.3 per 100,000 workers.

While ” Construction Helpers” are No. 6, the broader construction industry saw the highest total number of deaths (1,032), even if their per-capita rate is lower than loggers. Nearly 11% of fatal falls result from a height of 30 feet or higher.

Classroom discussion questions:

Ergonomics is an important part of job design (see Chapter 10 of your Heizer/Render/Munson text). How could it be used to improve safety in these jobs?
Can the physical environment be changed to make any of the jobs safer?

OM in the News: One Way to Power New AI Data Centers

Where is the energy to power the hundreds of new data centers that are popping up to run artificial intelligence demands coming from? “In the battle for AI dominance, every engine of the economy is getting recruited into the fight—including jet engines'” writes The Wall Street Journal (Feb. 18, 2026).

Jet engines are a natural fit. Power equipment giants GE Vernova, Siemens Energy, and Mitsubishi Heavy Industries already sell power turbines—known as aeroderivatives—that are modeled after these very jet engines. Aircraft engine companies such as GE Aerospace , Howmet Aerospace and Woodward also sell land-based aeroderivative turbines or components.

Yet designing the turbine, which keeps as much of the original jet engine features as possible, is a roughly 18-month undertaking. Instead, it only takes 30 to 45 days to convert a plane’s jet engine to a power-generating turbine. (There are 2 main modifications to convert an aircraft engine to a land-based natural gas turbine. One is replacing the fuel nozzles to utilize natural gas instead of jet fuel. The other is replacing the large fan on the front of the flight engine with a much smaller fan).

Retired aircraft, at an Air Force base near Tucson, Ariz

A company can remanufacture jet-engine parts with a few years of remaining life for use in power turbines, where they can operate for many additional years. Narrow-body jet engines experience higher stress from repeated takeoffs and landings. Power turbines can run as peakers—turning on only when demand surges—or continuously as baseload. Either way, they accumulate less wear and tear.

About 1,600 commercial aircraft engines are retired every year. If a third of those engines get converted into turbines, that would represent about 13 GW of capacity, or more than a quarter of the existing global natural gas turbine capacity.

AI-obsessed tech giants are planning to spend more than $700 billion in capital expenditures this year. The lure of that cash pile will generate a lot of creativity in the power sector.

Classroom discussion questions:

Why is there a need to convert jet engines?
Discuss the growth of data centers and the demands they create. (See our recent post on that topic.)

OM in the News: The Memory-Chip Shortage

Memory is one of the tech world’s most ubiquitous and essential components that come in 2 major types. DRAM handles more fleeting, immediate tasks like using apps. The other kind, called NAND flash memory, provides long-term storage for photos, videos and other data. And there has been a 7-fold increase in contract prices for DRAM and NAND flash in the past year.

Facing soaring memory-chip prices, the world’s biggest electronics companies are staring at a list of unpalatable responses:(1) charging consumers more, (2) eating the costs or (3) rejiggering product specs. Such is the supply-chain disruption wrought by the global drive into AI, which requires fleets of data centers with servers needing gargantuan amounts of memory, reports The Wall Street Journal (Feb. 13, 2026).

The memory crunch comes at an inopportune time for companies like Nintendo.

That has caused supply to dry up for the makers of smartphones, PCs, gaming consoles and various other electronic gadgets, and triggered a historic price uptick since early last year that is higher than any increase seen before.

Dell has raised prices for some commercial laptops by as much as 30%, while budget PCs from rival Acer now carry several gigabytes less of multitasking memory. Chinese smartphone maker Xiaomi recently discontinued the lower-memory variant of its new midtier device and raised prices. To summarize: A tough year for smartphones, PCs and game consoles is getting worse. Projected shipment declines are now stumbling deeper. PCs, with memory representing as much as 30% of their total costs, are particularly vulnerable.

With investments into AI infrastructure remaining hot, the prospects of memory prices falling soon don’t appear high. Supply is expected to remain tight through 2028.

Classroom discussion questions:

What is the underlying issue?
What can manufacturers of PCs, smartphones, and game consoles do to protect themselves?