So You Want To be a Drone Pilot

Image result for drone pilotBy Andrew Gunder, DCMME Graduate Assistant

Drones, over the past several years, have evolved to an extent that was once thought possible in only science fiction. Whether it be by land, sea, or air drones are redefining what is possible as well as how their implementation impacts companies and end users alike.

Today, they are rapidly expanding business process improvement in areas such as express shipping, delivery, site inspection, thermal imaging, geographic mapping, intelligence gathering, and many more.  While some processes involving drones can be automated, others still require a skillful human touch behind the controls to reduce risk and ensure quality. As a result, this has created a need for qualified drone operators for many businesses.

How do I become a drone pilot you ask? The process is actually quite simple. To obtain a drone pilot certification one must:

  • Be at least 16 years old
  • Be able to read, speak, write, and understand English
  • Be in a physical and mental condition to safely fly a drone
  • Pass the initial aeronautical knowledge exam​
  • Upon certification, must recertify every 2 years

Pilots are also required to carry their certification on them at all times during drone operation. Thankfully, for those interested in pursuing this certification path here at Purdue, you won’t have to go far to find a testing center for the FAA’s aeronautical knowledge exam. There is a testing center in West Lafayette at PURDUE AVIATION LLC at 1630 Aviation Drive. For additional details on becoming a drone pilot, you can visit the FAA’s website.



Is obtaining a drone pilot certification something you’d be interested in obtaining? Why or why not?

What other jobs could be augmented with drone technology?

What additional business processes can be improved through drone technology?


Manufacturing at the Speed of Light

Manufacturers are always looking for new ways to make their operations more efficient. One innovative new solution to do this might be using light manufacturing techniques. Light manufacturing techniques are useful for very small objects (think microns or nano-meters in length), which makes them excellent for the electronic industry where people are demanding smaller and smaller electrical components. As the demand for smaller electrical components increases, the cost of manufacturing these components also increases as the precision required by existing machines increases. There are two methods currently being used or researched that could make the process of manufacturing electrical components faster and, more importantly, less expensive.

The first technique is called “optoelectronic tweezers”. This method use optical traps (light) to move small objects into place and assemble the component in liquid and then freeze dries the liquid to allow the manufactured component to be removed. According to the article “New Approach Uses Light Instead of Robots to Assemble Electronic Components” this method could reduce the cost and improve the efficiency of making circuit boards and other small electronic devices. One of the benefits of this method is that it allows for massive parallel assembly meaning you could assembly multiple components at the same time, which improves the time it takes to manufacture bulk shipments of components.

The second technique, called “intense pulsed light sintering”, uses high-energy light to fuse nano-materials in a matter of seconds. The benefit compared to using lasers which accomplish the same thing is that the area of effect is nearly 7,000 times greater in the intense pulsed light sintering method than the typical laser method. The other benefit to this method over the existing pulsed light fusion technique is that it does not require as high a temperature to perform. Pulsed light fusion requires temperatures up to 250 degrees Celsius whereas this new method only requires temperatures up to 150 degrees Celsius. According to the article “Faster, cheaper, nano-based manufacturing”, engineers at Rutgers are currently developing this method for use in the manufacturing of thin films.



  1. When will these methods be available for manufacturers to start implementing into their processes?
  2. What other areas besides circuit boards and thin films could this technology be used in?
  3. How big of a bottom line impact could this technology have for manufacturers making these electronic components?




Kroger Robot centers coming soon

by Maria Hartas, DCMME Center Graduate Assistant

Kroger Co., the largest U.S. grocery retailer, in partnership with Ocado, a dedicated online grocery retailer, will be opening two high-tech customer fulfillment centers (CFCs) in the Central Florida and Mid-Atlantic regions. The facilities will be equipped with digital and robotic capabilities following Kroger’s first CFC, also known as a “shed”, which will be operating in Monroe, OH.

Kroger and Ocado are changing the retail-service industry by leveraging robotics technology in response to growing e-commerce purchasing habits. AI-enabled robots capable of quickly fulfilling high volume orders will efficiently supply click-and-collect orders, presumably in a more accurate, timely, and cot efficient assembly process.

With a commitment to build 20 CDCs, powered by Ocado, Kroger plans to advance the company’s ability to provide customers with anything, anytime and anywhere through the applications of AI and robotic technologies.

Can robots go grocery shopping?

How does AI advance e-commerce?

What is driving retail-service industry wide changes?


How AI can be applied within Supply Chain Management ? – by Abhilasha Satpathy, DCMME Center Graduate Student Assistant


  1. Chatbots for Operational Procurement:

Streamlining procurement related tasks through the automation and augmentation of Chabot capability requires access to robust and intelligent data sets, in which, the ‘procuebot’ would be able to access as a frame of reference; or it’s ‘brains’

As for daily tasks, Chatbots could be utilized to:

  • Speak to suppliers during trivial conversations.
  • Set and send actions to suppliers regarding governance and compliance materials.
  • Place purchasing requests.
  • Research and answer internal questions regarding procurement functionalities or a supplier/supplier set.
  • Receiving/filing/documentation of invoices and payments/order requests (Smith 2016).


2.Machine Learning (ML) for Supply Chain Planning (SCP)

Supply chain planning is a crucial activity within SCM strategy. Having intelligent work tools for building concrete plans is a must in today’s business world.ML, applied within SCP could help with forecasting within inventory, demand and supply. If applied correctly through SCM work tools, ML could revolutionize the agility and optimization of supply chain decision-making.By utilizing ML technology, SCM professionals — responsible for SCP — would be giving best possible scenarios based upon intelligent algorithms and machine-to-machine analysis of big data sets. This kind of capability could optimize the delivery of goods while balancing supply and demand, and wouldn’t require human analysis, but rather action setting for parameters of success.

  1. Machine Learning for Warehouse Management

Taking a closer look at the domain of SCP, its success is heavily reliant on proper warehouse and inventory-based management. Regardless of demand forecasting, supply flaws (overstocking or under stocking) can be a disaster for just about any consumer-based company/retailer.ML provides an endless loop of forecasting, which bears a constantly self-improving output. This kind of capabilities could reshape warehouse management as we know today.

  1. Autonomous Vehicles for Logistics and Shipping

Intelligence in logistics and shipping has become a center-stage kind of focus within supply chain management in the recent years. Faster and more accurate shipping reduces lead times and transportation expenses, adds elements of environmental friendly operations, reduces labor costs, and — most important of all — widens the gap between competitors.

If autonomous vehicles were developed to the potential — that certain business analysts and tech gurus have hypothesized — the impact on logistics optimization would be astronomical.

“Where drivers are restricted by law from driving more than 11 hours per day without taking an 8-hour break, a driverless truck can drive nearly 24 hours per day. That means the technology would effectively double the output of the U.S. transportation network at 25 percent of the cost” ( 2016).

  1. Natural Language Processing (NLP) for Data Cleansing and Building Data Robustness

NLP is an element of AI and Machine Learning, which has staggering potential for deciphering large amounts of foreign language data in a streamlined manner.

NLP, applied through the correct work took, could build data sets regarding suppliers, and decipher untapped information, due to language barrier. From a CSR or Sustainability & Governance perspective, NLP technology could streamline auditing and compliance actions previously unable because of existing language barriers between buyer-supplier bodies (greenbiz 2017).

  1. ML and Predictive Analytics for Supplier Selection and Supplier Relationship Management (SRM)

Supplier selection and sourcing from the right suppliers is an increasing concern for enhancing supply chain sustainability, CSR and supply chain ethics. Supplier related risks have become the ball and chain for globally visible brands. One slip-up in the operations of a supplier body, and bad PR is heading right towards your company.

But, what if you had the best possible scenario for supplier selection and risk management, during every single supplier interaction?

Data sets, generated from SRM actions, such as supplier assessments, audits, and credit scoring provide an important basis for further decisions regarding a supplier. With the help of Machine Learning and intelligible algorithms, this (otherwise) passive data gathering could be made active. Supplier selection would be more predictive and intelligible than ever before; creating a platform for success from the very first collaborations. All of this information would be easily available for human inspections but generated through machine-to-machine automation; providing multiple ‘best supplier scenarios’ based on whatever parameters, in which, the user desires.


Community, K. R. (2017, October 26). 6 Applications of Artificial Intelligence for your Supply Chain. Retrieved from



  1. How will AI and autonomous vehicles transform supply chains as we know them?
  2. How does AI help in predictive analysis?
  3. How will Machine Learning change supply chain planning?




Microsoft HoloLens 2 Release Details

Microsoft is going to announce and show off its HoloLens 2 at the Mobile World Congress on February 24th.

Here’s what to expect from the new HoloLens:

1.) The price point is expected to be roughly the same compared to the original HoloLens, which was $3,000 for the base model and $5,000 for the commercial model.

2.) There will be new Artificial Intelligence (AI) technology introduced. Little detail has been revealed about the AI tech and what its capabilities will be when integrated with the HoloLens 2.

3.) Improved Hologram graphics. The graphics are expected to be clearer and up to date compared to the previous HoloLens.

4.) A better processor will be installed to handle the AI and the improved hologram graphics. In addition to this, there will be less delay in response time when using the HoloLens 2.

5.) There’s a possibility of a new design and couple of additional features. These new features are still unknown, but rumor has it the material might be different and lighter weight.

Confirmed details will be released in next Thursday’s blog post after the Mobile World Congress on February 24th.

Will the new HoloLens be incorporated into the market for more commercial uses?

What new sensors will be added to the HoloLens for better use and more applications of the tool?

What additional uses will the new HoloLens 2 have when AI is incorporated into the device?


Military Uses AI Technology for Drone Applications

The US Army is increasing its use of drones to expand and improve capabilities and awareness on the battlefield. This use of drone technology is apart of the Army’s initiative to integrate emerging technologies such as AI (Artificial Intelligence), better resolution sensors, and faster processing speeds of computers.

They’re using a “MacBook” size tablet to operate multiple drones because of a new operational infrastructure backbone developed in a partnership with MAG Aerospace. This technical blueprint system is owned by the Army and will allow soldiers to have quicker access to each drone, which will be incredibly useful in combat environments where live and instant video feeds are important.

The drones will also be able to operate on their own with the use of AI technology and can also be operated by the soldiers on the ground if needed. AI technology and the use of drones are making huge strides in development and use for military applications.

Will this technology be incorporated into the consumer market in the near future?

How can this technology be used in supply chain and operations for business applications?

Will there be additional applications for drones with further development of AI technology?


Disruptive Innovations and their applications in Supply Chain Management – by Abhilasha Satpathy, DCMME Center Graduate Student Assistant

Procurement and supply chain are at the cusp of a disruption with AI, IoT and blockchain technology. A digital transformation is ensuing with the promise of greater efficiency in business processes, operations, transparency and security.

Spend analysis

Spend analysis used in strategic sourcing, needs a shift from the traditional descriptive analytics model to more predictive and prescriptive analytics. Organizations can develop tools to enhance their spend analysis with public domain data — from social media, weather data, demographics, suppliers, competition and logistics to name a few — to help uncover insights that can save money and improve supply chain.


Supplier lifecycle management

The traditional supplier lifecycle management platform, when augmented by big data from the public domain, can offer meaningful information on suppliers and supply chain risks. An IoT solution can be employed to track the quality of the product at various stages of the supply chain thus improving the efficiency in the process and providing the metrics for supplier evaluation.


Strategic sourcing

Supplier bids are collected using online sourcing events, but a large part of the sourcing evaluation and award process is manual in nature. Using blockchain for through all steps of the process — proposals, quotes and bids — or auction, can offer greater efficiency and transparency.


Contract management

A blockchain platform and its smart contract framework coupled with IoT and AI, can help facilitate greater efficiency in compliance and obligation management. AI can help develop smart wizards to build contracts based on responses to specific questions and can further be enabled for pattern recognition to identify changes to standard clauses or introduction of non-standard clauses.

Order management

The traditional order management system is internal to any organization and facilitates the fulfillment process. Blockchain platform powered with AI and IoT can drive greater efficiency in orchestrating and streamlining purchase orders, shipment details, trade documents, goods receipts, quality assurance documents, returns and accounting.


The logistics industry is an early adopter of AI, IoT and Blockchain, and is already reaping great business benefits. IoT in the logistics ecosystem can provide great insights on inventory management, shelf life, storage temperature, delivery routes, real-time tracking of freight and more





  1. How are AI, IOT and blockchain transforming the logistics industry?
  2. How is blockchain helping in order management?
  3. How can AI help in contract management ?