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3D Printing is Finally Changing the Manufacturing Landscape

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3D Printing is Finally Changing the Manufacturing Landscape

3D Printing is Finally Changing the Manufacturing Landscape

The right software can change industries quickly.

For fast-moving companies like Airbnb, Stripe, Uber, Facebook, or Slack, the piping – such as the internet and smartphones – is already well-established, allowing these startups to scale at unprecedented speeds.

For 3D printing and other such “hard” technologies? Things end up being a lot more complicated.

A Long Time Coming

The rise of 3D printing reached peak hype years ago – and as far back as 2014, we were illustrating how 3D printing could ultimately shape the future of business. However, since those days, the technology has arguably fallen into the dreaded “trough of disillusionment” category on the famous Gartner Hype Cycle.

The harsh reality is that it’s just really hard to move things like 3D printing forward at the same type of speed as software. For the technology to scale at a commercial level, products would need to be flawless and intuitive from the get-go (they weren’t), and all engineering, technological, and design problems would need to be solved at lightning-quick speeds. Instead, it takes huge amounts of research, investment, patience, and iterations to get to the next level.

Today’s infographic comes to us from Raconteur, and it highlights a most recent snapshot of the 3D printing industry. Importantly, it shows that the technology is still chugging along in a way that is changing how things are made – just at a less hype-worthy pace.

Building From Ground Up

3D printing has now permeated practically every industry in at least some capacity, being used in a wide range of sectors from consumer goods to pharmaceuticals.

According to a report by EY, the potential for additive manufacturing is highest in the automotive and aerospace industries. For example, it’s expected that about half (49%) of automotive companies will use 3D printing to directly manufacture car parts in order to achieve operational efficiencies. These companies believe that 3D printing will help them address challenges such as demand for increased customization, continued improvement, and lightweight components.

As a result of increased demand and more familiarity with the technology, Gartner said shipments of 3D printers increased 108% between 2015 and 2016, resulting in 456,000 units shipped globally. More importantly, by 2020 this number will be at 6.7 million units, which would represent phenomenal growth for the technology.

As of today, most companies are still using 3D printers for accelerating product development, such as prototyping (34% of applications) and for proof of concept (23%). However, as 3D printing gets more use in additional areas – such as mass customization and collaboration on products – it’s possible the ship will really begin to sail, even if it was slightly delayed in getting out of the gate.

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Data Visualization

Assembling the World Country-by-Country, Based on Economy Size

How does the world map change if it gets assembled based on the size of economies, in ascending order of GDP or GDP per capita?

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If you had to sketch a world map, you’d probably start with a place that is familiar.

Perhaps you would begin by drawing your own continent, or maybe you’d focus on the specific borders of the country you live in. Then, you’d likely move to drawing the outlines of neighboring countries, eventually working your way to far and distant lands.

This would be a logical way for anyone to think about such a task, and it gives some insight as to how humans think about the world.

We start with what’s familiar, and build it out until it’s a complete picture.

Assembling the World by Economy Size

What if we assembled a world map in a completely different order?

Today’s two animations come to us from Engaging-Data, and they approach the world map from an alternate angle: assembling countries on the map in the order of their economic footprints.

GDP (Nominal)

The first map, shown below, uses nominal GDP to assemble countries in ascending order:

Country GDP

This version of the map shows the smallest economies first, with the larger economies at the end.

For this reason, the first economies appearing on the map tend to be developing nations, or nations with smaller geographical or demographic footprints.

For example, even though the Falkland Islands are wealthy on a per capita basis, the British Overseas Territory has fewer than 4,000 people, which gives it a minor footprint on a global stage.

GDP per Capita (Nominal)

Now, let’s take a look at the same map, constructed in order of GDP per capita:

Country GDP per Capita

This animation is more cohesive, given that it is not dependent on population size. Instead the order here is based on economic output (in nominal terms) of the average person in each country or jurisdiction.

In this case, developing nations appear first – and at the end, more developed regions (like Europe and North America) tend to fill out.

Note: All rankings here are in nominal terms, which use market rates to calculate comparable values in U.S. dollars, while omitting the cost of living as a factor. GDP rankings change significantly when using PPP rates.

Other Ways to Assemble the World

While assembling nations based on GDP provides an interesting way to look at the world, this same approach can be tried by applying other statistics as well.

We recommend checking out this page, which allows you to “assemble the world” based on measures like population density, life expectancy, or population.

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Maps

Mapped: The Salary Needed to Buy a Home in 50 U.S. Metro Areas

The annual salary needed to buy a home in the U.S. ranges from $38k to $255k, depending on the metropolitan area you are looking in.

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The Salary Needed to Buy a Home in 50 U.S. Metro Areas

Over the last year, home prices have risen in 49 of the biggest 50 metro areas in the United States.

At the same time, mortgage rates have hit seven-year highs, making things more expensive for any prospective home buyer.

With this context in mind, today’s map comes from HowMuch.net, and it shows the salary needed to buy a home in the 50 largest U.S. metro areas.

The Least and Most Expensive Metro Areas

As a reference point, the median home in the United States costs about $257,600, according to the National Association of Realtors.

 Median Home PriceMontly Payment (PITI)Salary Needed
National$257,600$1,433.91$61,453.51

With a 20% down payment and a 4.90% mortgage rate, and taking into account what’s needed to pay principal, interest, taxes, and insurance (PITI) on the home, it would mean a prospective buyer would need to have $61,453.51 in salary to afford such a purchase.

However, based on your frame of reference, this national estimate may seem extremely low or quite high. That’s because the salary required to buy in different major cities in the U.S. can fall anywhere between $37,659 to $254,835.

The 10 Cheapest Metro Areas

Here are the cheapest metro areas in the U.S., based on data and calculations from HSH.com:

RankMetro AreaMedian Home PriceMonthly Payment (PITI)Salary Needed
#1Pittsburgh$141,625$878.73$37,659.86
#2Cleveland$150,100$943.55$40,437.72
#3Oklahoma City$161,000$964.49$41,335.41
#4Memphis$174,000$966.02$41,400.93
#5Indianapolis$185,200$986.74$42,288.92
#6Louisville$180,100$987.54$42,323.15
#7Cincinnati$169,400$1,013.37$43,429.97
#8St. Louis$174,100$1,031.70$44,215.56
#9Birmingham$202,300$1,040.51$44,593.35
#10Buffalo$154,200$1,066.29$45,698.05

After the dust settles, Pittsburgh ranks as the cheapest metro area in the U.S. to buy a home. According to these calculations, buying a median home in Pittsburgh – which includes the surrounding metro area – requires an annual income of less than $40,000 to buy.

Just missing the list was Detroit, where a salary of $48,002.89 is needed.

The 10 Most Expensive Metro Areas

Now, here are the priciest markets in the country, also based on data from HSH.com:

RankMetro AreaMedian Home PriceMonthly Payment (PITI)Salary Needed
#1San Jose$1,250,000$5,946.17$254,835.73
#2San Francisco$952,200$4,642.82$198,978.01
#3San Diego$626,000$3,071.62$131,640.79
#4Los Angeles$576,100$2,873.64$123,156.01
#5Boston$460,300$2,491.76$106,789.93
#6New York City$403,900$2,465.97$105,684.33
#7Seattle$489,600$2,458.58$105,367.89
#8Washington, D.C.$417,400$2,202.87$94,408.70
#9Denver$438,300$2,139.02$91,672.45
#10Portland$389,000$1,987.37$85,173.08

Topping the list of the most expensive metro areas are San Jose and San Francisco, which are both cities fueled by the economic boom in Silicon Valley. Meanwhile, two other major metro areas in California, Los Angeles and San Diego, are not far behind.

New York City only ranks in sixth here, though it is worth noting that the NYC metro area extends well beyond the five boroughs. It includes Newark, Jersey City, and many nearby counties as well.

As a final point, it’s worth mentioning that all cities here (with the exception of Denver) are in coastal states.

Notes on Calculations

Data on median home prices comes from the National Association of Realtors and is based on 2018 Q4 information, while national mortgage rate data is derived from weekly surveys by Freddie Mac and the Mortgage Bankers Association of America for 30-year fixed rate mortgages.

Calculations include tax and homeowners insurance costs to determine the annual salary it takes to afford the base cost of owning a home (principal, interest, property tax and homeowner’s insurance, or PITI) in the nation’s 50 largest metropolitan areas.

Standard 28% “front-end” debt ratios and a 20% down payments subtracted from the median-home-price data are used to arrive at these figures.

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