Japanese start-up introduces the first humanless warehouse

Jobs performed by warehouse workers and forklift operators are now completed by robots in the first humanless warehouse in Tokyo. Mujin, a start-up company, has equipped its customer’s, JD.com, e-commerce warehouse with robots.

In an effort to augment existing industrial robot arms, Mujin is building robot controllers and camera systems. The controller’s technology based on motion planning and computer vision, strengthens robotic autonomous and intelligent action. The enhanced controllers lead to the elimination of manual robot training and overall higher productivity.

The 40,000-sq-m JD.com e-commerce facility is equipped with 20 industrial robots that complete tasks such as picking, transferring packages, and loading docks and trucks. Crates on conveyor belts, camera systems and Mujin robot controllers are all part of the humanless warehouse. The robots come with five workers who are needed to service the machines, compared to an estimated 400 to 500 workers that would be needed in the absence of the robots.

Mujin is targeting the predictability in the controller’s moves, and the development of automation technologies such as robot hardware, sensing hardware, AI algorithms, conveyor systems and sorting systems. That’s to say that the company aims to standardize a complete automation package that can automate warehouses without tailored components for customers.

Improvements will continue to be made in the field of warehouse automation as Japanese companies, following JD.com, will be testing out the new technology.

What level of engagement do workers have in a fully automated warehouse?

How are robots enhancing productivity in a warehouse?

What technologies can aid the integration of robots in a warehouse?



Understanding Smart Manufacturing

In the article What is Smart Manufacturing? the author delves into what exactly smart manufacturing is, as defined by the new technology that has allowed it to come into being.  Smart manufacturing has enabled us to use continuously collected and flowing data to continuously improve processes thus taking some the human error element out of manufacturing.  It’s not to say that the smartest piece in the manufacturing puzzle isn’t still a human because it most certainly is.  It is more a realization that machines can now collect and interpret data themselves (as we have programmed them) so that they almost “think” on their own.

The author points out that some believe we are now in the 4th industrial revolution.  This industrial revolution involves big data, predictive analytics, and the artificial intelligence created using these concepts.  In essence, the data tells us what to do.  Instead of a maintenance cycle that works based on past failures, think of a maintenance cycle that continuously collects data thus giving us indicators before a failure.  Furthermore, the data can let us know what failed as well which increases efficiency.  This connection is known as the IIoT – the Industrial Internet of Things.  The emergence of cheap connected devices, coupled with the availability and affordability of mass computing power, has been the biggest driver of Smart Manufacturing.

Visibility is a big driver in understanding ROI in smart manufacturing.  The processes can alert users via messages on their phones; displays on a monitor, or a number of other ways.  Communication between machine and humans becomes simple.  When the data tells you what to do, decisions normally become easier thus reducing human error, increasing efficiencies in manufacturing processes, and finally saving money.


Will smart manufacturing eventually become so good that actual human jobs are lost?

What safeguards are in place so we know that sensors on manufacturing processes are not relaying operators the wrong data?

As I mentioned in a previous blog, do you believe there is a downside to collecting too much data?




The IoT will Give us the Big Data of The Future

In the article Big Data Analytics: The Force Behind the Next Internet of Things Wave, the author delves into how the cutting edge of the IoT is giving us the Big Data that will shape our future.  With more devises in more place, more data is being collected and thus more data must be analyzed.  The true value in this Big Data is our ability to make sense of it consequently create value.  The author examines a number of case where cutting edge sensors are allowing the IoTs to collect data that drives increased performance, predictive ability, and cost savings.

One of the first places the IoTs really took off was in our own homes.  Smart devices collecting data from meters, data on demographics, and data on energy consumption have helped customers save energy and money.  One smart meter company actually saved its customers over $500 million in energy spending.  With data analytics, forward-thinking energy management companies are able to run analyses on consumer thermostat data to better understand energy usage patterns.

Another case presented is that of an energy company using sensors in its oil and gas wells. The company collected data about the average production of oil, gas, and water from each of its wells.  It combined it with historical well performance and geospatial data to look at efficiencies and deficiencies based on location and equipment.  Based on the combination of this data and the sharing of this data with its operations, the company experienced 126 million per year in incremental revenue.


What are everyones thoughts on when we will begin to be fully connected, that is, when almost every device and thing we use is connected to each other?

Do you think we are collecting too much data?

As a customer, at what point do you believe collecting your data is an infringement on your privacy?  Is there any real way to track such invasions of privacy?


Inventec to set up smart factory in Southeast Asia in 2016

An article published on August 27th, 2015 in The China Post (http://www.chinapost.com.tw/taiwan/business/2015/08/27/444353/Inventec-to.htm) describes how Inventec, a major Taiwanese supplier of the Chinese phone brand Xiaomi, is planning on building a smart manufacturing plant in Southeast Asia in 2016. The new smart facility will manufacture smart phones and PC related products. But according to Inventec Chairman Richard Lee, “We’re not going to copy our traditional labor-intensive Chinese factories.” Their plan is to utilize the “Industry 4.0” model and to use Web-based intelligent computer systems. Inventec recently signed a letter of intent with Siemens PLM Software to upgrade their current and future plants with these Web-based intelligent computer systems. To date they have purchased 300 robotic arms, but they expect to purchase another 3,000 more by June of 2016, which will cost approximately US$20 million to US$30 million. Their goal is to manufacture more efficiently by creating “a networked, flexible, and dynamically self-organizing manufacturing process for highly customizable products.” This is a great example of how Smart Manufacturing is changing the way that Chinese and Southeast Asian companies have traditionally approached manufacturing. Will it be difficult for China and Southeast Asian countries to shift from labor intensive factories to smart factories? Does smart manufacturing have a future in China and Southeast Asia? How will the work force feel about this upgraded technology? Will smart manufacturing in China and Southeast Asia have a significant impact on countries who import from them?