Automation in Manufacturing by Abhilasha Satpathy, DCMME Center Graduate Student Assistant

Three types of automation in production can be distinguished: (1) fixed automation, (2) programmable automation, and (3) flexible automation.

Fixed automation, also known as “hard automation,” refers to an automated production facility in which the sequence of processing operations is fixed by the equipment configuration. In effect, the programmed commands are contained in the machines in the form of cams, gears, wiring, and other hardware that is not easily changed over from one product style to another. This form of automation is characterized by high initial investment and high production rates. It is therefore suitable for products that are made in large volumes. Examples of fixed automation include machining transfer lines found in the automotive industry, automatic assembly machines, and certain chemical processes.

Programmable automation is a form of automation for producing products in batches. The products are made in batch quantities ranging from several dozen to several thousand units at a time. For each new batch, the production equipment must be reprogrammed and changed over to accommodate the new product style. This reprogramming and changeover take time to accomplish, and there is a period of nonproductive time followed by a production run for each new batch. Production rates in programmable automation are generally lower than in fixed automation, because the equipment is designed to facilitate product changeover rather than for product specialization. A numerical-control machine tool is a good example of programmable automation. The program is coded in computer memory for each different product style, and the machine tool is controlled by the computer program. Industrial robots are another example.

Flexible automation is an extension of programmable automation. The disadvantage with programmable automation is the time required to reprogram and change over the production equipment for each batch of new product. This is lost production time, which is expensive. In flexible automation, the variety of products is sufficiently limited so that the changeover of the equipment can be done very quickly and automatically. The reprogramming of the equipment in flexible automation is done off-line; that is, the programming is accomplished at a computer terminal without using the production equipment itself. Accordingly, there is no need to group identical products into batches; instead, a mixture of different products can be produced one right after another.

References:

(n.d.). Numerical control. Retrieved from https://www.britannica.com/technology/automation/Numerical-control

Questions:

  1. What are the different forms of automation in manufacturing?
  2. How is flexible automation different from programmable automation?
  3. What is are the disadvantages of programmable automation?

 

 

Big Data Technology: Impact on supply chains

Sources

https://www.supplychaindive.com/news/what-Big-Data-supply-chain-application-primer/435865/

https://www.mckinsey.com/business-functions/operations/our-insights/big-data-and-the-supply-chain-the-big-supply-chain-analytics-landscape-part-1

 

What is Big Data

Big Data as a concept requires three distinct layers before application: more data, processing systems, and analytics. If Big Data only recently entered the supply chain management spotlight, then, it may be because the technology only recently reached the last layer to deliver insights.

Information processing

Businesses are no stranger to data; supply chain managers have been producing reports, tracking trends and forecasting for decades. So when data exploded to become Big Data, companies were quick to rise to the challenge of collecting it for future use.

“What the CIOs and IT organizations were asked to do, early part of this decade – probably even the latter half of the last decade – was ‘hey there’s a lot of value in data, let’s actually keep on collecting data,’” Suresh Acharya, Head of JDA Labs told Supply Chain Dive.

But even if a pedometer generates bits and bytes each second, the information created remains unpalatable unless it is stored with previous data to be analyzed over time.

Therein came the need for information processing systems more powerful than spreadsheets.  Many of these are now known by their three letter acronyms (e.g. ERP, CRM, TMS or WMS), but their purpose is similar: to store, collect and simplify information for the average user. Such processors became so ubiquitous, it is now common for a company to boast nine or ten distinct systems supporting supply chain management in a single plant.

Insight and decision-making: The next frontier

There’s a new wave of data processors on the market promising to reap the benefits of Big Data for supply chains.

Supply chain solutions companies often offer to integrate the various systems from the previous generation, allowing companies to visualize data sets at each corporate level for the increased granularity and analytical capacity desired from Big Data.

Yet, Big Data is not only the ability to process more information, but the ability to innovate, automate and use data for enhanced decision-making. The toolkit is meant to be applied, not simply possessed.

A look back at our pedometer example may help illustrate the difference between having a software solution and actively unpacking Big Data. At first, the pedometer could only track information – making it a data generator. If connected to the Cloud and transmitting to a data processor, the device could be considered as helping to generate Big Data. But it was never a Big Data device because it never actively helped a user make decisions.

Meanwhile, the Fitbit – which tracks steps, heart rates and other biometrics – can analyze and apply the data it collects to guide the wearer to better health habits; for example, it alerts the user when they have been sitting too long and reminds them to go take a walk.

 

 

Big Data applications in supply chain

Manufacturing

Big data and analytics can already help improve manufacturing. For example, energy-intensive production runs can be scheduled to take advantage of fluctuating electricity prices. Data on manufacturing parameters, like the forces used in assembly operations or dimensional differences between parts, can be archived and analyzed to support the root-cause analysis of defects, even if they occur years later. Agricultural seed processors and manufacturers analyze the quality of their products with different types of cameras in real-time to get the quality assessments for each individual seed.

The Internet of Things, with its networks of cameras and sensors on millions of devices, may enable other manufacturing opportunities in the future. Ultimately, live information on a machine’s condition could trigger production of a 3D-printed spare part that is then shipped by a drone to the plant to meet an engineer, who may use augmented reality glasses for guidance while replacing the part.

Warehousing

Logistics has traditionally been very cost-focused, and companies have happily invested in technologies that provide competitive advantage. Warehousing in particular has seen many advances using available ERP data. One example are “chaotic” storage approaches that enable the efficient use of warehouse space and minimize travel distances for personnel. Another are high-rack bay warehouses that can automatically reshuffle pallets at night to optimize schedules for the next day. Companies can track the performance of pickers in different picking areas to optimize future staff allocation.

New technologies, data sources and analytical techniques are also creating new opportunities in warehousing. A leading forklift provider is looking into how the forklift truck can act as a big data hub that collects all sorts of data in real time, which can then be blended with ERP and Warehouse Management System (WMS) data to identify additional waste in the warehouse process. For example, the analysis of video images collected by automated guided vehicles, along with sensor inputs including temperature, shelf weight, and the weight on the forklift, can be used to monitor picking accuracy, warehouse productivity and inventory accuracy in real time. Similarly forklift driving behavior and route choices can be assessed and dynamically optimized to drive picking productivity. The data can also be used to conduct root-cause analysis of picking errors by shape, color, or weight, to help to make processes more robust.

New 3D modelling technologies can also help to optimize warehouse design and simulate new configurations of existing warehouse space to further improve storage efficiency and picking productivity. German company Logivations, for example, offers a cloud-based 3D warehouse layout planning and optimization tool.

Transportation

Truck companies already make use of analytics to improve their operations. For example, they use fuel consumption analytics to improve driving efficiency; and they use GPS technologies to reduce waiting times by allocating warehouse bays in real time.

Courier companies have started real-time routing of deliveries to customers based on their truck’s geo-location and traffic data. UPS, for example has spent ten years developing its On-Road Integrated Optimization and Navigation system (Orion) to optimize the 55,000 routes in the network. The company’s CEO David Abney says the new system will save the company $300 million to $400 million a year3.

Big analytics will also enable logistics providers to deliver parcels with fewer delivery attempts, by allowing them to mine their data to predict when a particular customer is more likely to be at home. On a more strategic basis, companies can cut costs and carbon emissions by selecting the right transport modes. A major CPG player is investing in analytics that will help it to understand when goods need be shipped rapidly by truck or when there is time for slower barge or train delivery.

Point of Sale

Brick and mortar retailers—often under heavy pressure from online competitors that have mastered analytics—have understood how data driven optimization can provide them with competitive advantages. These techniques are being used today for activities like shelf-space optimization and mark-down pricing. Advanced analytics can also help retailers decide which products to put in high value locations, like aisle ends, and how long to keep them there. It can also enable them to explore the sales benefits achieved by clustering related products together.

Search engine giant Google has acquired Skybox, a provider of high resolution satellite imagery, that can be used to track cars in the car park in order to anticipate in-store demand. Others have explored the use of drones equipped with cameras to monitor on-shelf inventory levels.

Questions:

Q) What role can Big Data play in the optimization of Supply Chains across industries?

Q) What are the cost implications in companies leveraging big data to organize their supply chains?

Q) How is Big data different from data analytics?

 

 

How disruptive technologies are improving food supply chains by Abhilasha Satpathy, DCMME Center Graduate Student Assistant

One of the lectures in my Logistics class, got my interest in understanding how we as professionals interested in the supply chain industry can do our bit to improve the efficiencies in the food supply chain area and I decided to do some reading on the same. I decided that since it’s the need of the hour, maybe I can share it with others too.

IOT enabling better decisions

Internet of Things (IoT) or sensors can continuously capture large amounts of relevant information, while the decreasing cost of storing data in cloud solutions, and the increased possibilities of analysing these big amounts of data, creates new insights and the basis for better decisions. For example, the sensors can capture data in biological processes, such as aquaculture. Advanced analytics on these data may create new insights and better decisions. They may contribute to improved fish health and fish welfare, reduced mortality rates, improved feed efficiency and a more sustainable seafood production.Moreover, IoT enables the entire food and beverage industry to monitor raw goods and products all the way through the value chain, and use the information to ensure safe and sustainable products at the consumers’ tables.

Use of blockchain

Blockchain and other digital technologies will enable the communication of information from sensors directly to the consumer at the purchasing moment. Digital assurance may contribute to making the story true and trustable and an effective defence against counterfeiting and food fraud.For example, the food service industry may log and blockchain temperature information of products throughout the supply chain, from the ready meal producer to the consumer in the convenience store. In addition to the value of this information to the consumer, this may also contribute to longer shelf lives, improved cooling chain performance and reduced food waste. The flip side of making this information fully transparent to the consumer, is of course that the consumer will also know if the cooling chain was disrupted.

Shorter value chains

Thirdly, the platform economy may disrupt the supply chain and impact the retailers by connecting the consumers more directly to the food producers, as short value chains or direct purchase become consumer values in themselves. The decrease in transaction cost and the growing e-business in the food market, may increase the power of consumers, as a larger variety of products and producers may be made available at a lower cost. In addition to deep customer insight, platforms and social media creates open innovation opportunities, by involving customers directly in product development. Through engagement, sense of belonging and loyalty your customers may increasingly become part of your brand.

Transportation Automation

Transportation planners are on the frontlines of the latest supply chain disruption — and they’re making significant progress in more ways than one. Although many think of autonomous vehicles when it comes to the next generation of transportation, supply chain managers have a myriad of applications for advanced robotics and automated systems:

  • Smart Traffic Management: The city of Nanjing, China recently introduced a traffic flow management system that incorporates real-time data as well as predictive analytics and forecasts to help travelers plan their routes on a day-to-day basis. Such a system is easily extrapolated to the supply chain by providing information on traffic delays, detours and even weather conditions.
  • Enhanced Safety Mechanisms: While some are concerned with the safety issues presented by autonomous and driverless vehicles, others focus on human drivers. New systems can estimate a driver’s fatigue by monitoring various vital signs to help avoid accidents on the road.
  • Aerial Drone Delivery: Remote-controlled aerial drones are already popular among consumers, so it makes sense that they’re being considered for product deliveries and shipments.

 

References:

https://www2.deloitte.com/content/dam/Deloitte/ie/Documents/ConsumerBusiness/2015-Deloitte-Ireland-Food_Value_Chain.pdf

(n.d.). How Are Digital Technologies Transforming Food Value Chains? Retrieved from https://www.mygfsi.com/news-resources/news/news-blog/1330-how-are-digital-technologies-transforming-food-value-chains.html

Nichols, M. R. (2018, April 25). 5 Technologies Disrupting the Supply Chain. Retrieved from https://www.manufacturing.net/article/2018/04/5-technologies-disrupting-supply-chain

Questions:

  1. How is IOT changing the food supply chains as we know it?
  2. How can transportation automation help improve the efficiency of food supply chains?
  3. How will shorter value chains enhance the efficiencies of food supply chains world over?

 

 

Digital twins in supply chain

What is a digital twin

A digital twin is a virtual image/software representation of a real product, process, asset or service. For example, a digital visualization of an organ used to simulate an upcoming operation. A digital copy can be used for monitoring and control, as well as for planning and forecasting the outcomes of various scenarios. This makes it possible to understand, predict and optimize performance.

For the digital twin to be truly a twin, all available information/data must be linked one-to-one. In some cases, individual digital twins are connected to each other in order to reproduce and optimize twins of an entire construct.

Advantages of digital twins

he benefits that digital twin technologies offer your business include:

  • Increased reliability of equipment and production lines
  • Improved OEE through reduced downtime and improved performance
  • Improved productivity
  • Reduced risk in various areas including product availability, marketplace reputation, and more
  • Lower maintenance costs by predicting maintenance issues before breakdowns occur
  • Faster production times
  • New business opportunities such as mass customisation, mixed manufacturing, small-batch manufacturing, and more
  • Improved customer service as customers can remotely configuring customised products
  • Improved product quality, and enhanced insight into the performance of your products, in multiple real-time applications and environments
  • More efficient supply and delivery chains
  • All the above combined will result in the ultimate benefit of improved profits

 

How do digital twins work and where can they be used?

Digital twins act as a bridge between the physical and digital world. With the help of intelligent sensors integrated into physical elements, all necessary data can be captured and transmitted. In conjunction with relevant business data, this data is then analyzed and, in the best case scenario, can uncover opportunities that may otherwise have gone undetected.

NASA has been using digital twins for many years. This is mainly because the systems it needs to monitor are located at an unattainable distance. John Vickers, NASA’s leading manufacturing expert and manager of the NASA National Center for Advanced Manufacturing, describes NASA’S vision to be able to create, test and build their equipment in a virtual world in the future.

Installing IoT sensors can not only help the company itself, but also increase the efficiency of  its supply chain partners and prevent possible disruptions. But where can digital twins be used in practice? Practically everywhere: You can recognize existing customer requirements, simulate the effects of corresponding trends and thus obtain a comprehensive view of the broad spectrum of customers. In production, current state analyses can be carried out, adjustments can be made if necessary and untapped potential can be identified. In logistics, digital twins can be used to optimize stocks and to track and monitor them through geolocation. Digital twins enable companies to meet their supply chain partners’ requirements to the best of their abilities .

What does the future look like?

Forbes describes the current state of digital twin technology as the threshold to a digital explosion in which significantly more companies will develop and introduce their own digital twins in the future based on success stories of others. The number of digital representatives of physical objects is estimated to be in the billions, which simultaneously opens up the opportunity for cooperation between product experts and data scientists. Gartner predicts that by 2021, half of the major industrial companies will be using digital twins, resulting in an average efficiency increase of 10%.

In addition, experts predict that future developments will be much more likely to involve the combination of individual twins than at present. The fact that the use of digital twins can open up new business fields and models arouses curiosity about the unknown potential of innovative solutions in the future.

Amazon delivery tents

by Maria Hartas, DCMME Graduate Assistant

When looking into ways to expand its logistics operations, Amazon is embracing a “carnival” tent solution. As the company races to keep up with competitors, such as UPS, FedEx and USPS, Amazon has set up fabric tents in at least eight states; Tennessee, South Carolina, Arkansas, Georgia, Colorado, Louisiana, Kentucky and Idaho. These tents operate as temporary delivery stations used for housing and sorting packages before they’re final delivery.

 Why tents?

Amazon ships billions of items annually; the company reported 5 billion items shipped with Prime alone in 2017. According to Amazon’s SEC filling, the costs associated with the delivery of all online orders received are growing exponentially as eCommerce activity continues to increase. As Amazon has recruited more deliver service partners (DSPs) to grow the company’s last-mile logistics network, a tent that takes a couple weeks to build enables the rapid expansion in new areas.

The tents are large enough, starting up to 35 feet tall and ranging between 9,000 square feet and 18,000 square feet, and can adequately accommodate up to 300 people. With little-to-no property taxes and little maintenance required, tents are well positioning Amazon to compete in getting closer to customers.

What are the benefits of building tents?

Are tents solving last-mile delivery problems?

Can delivery tents offer Amazon a sustainable competitive advantage?

Sources:

https://www.businessinsider.com/amazon-pitches-carnival-tents-race-catch-up-ups-fedex-2019-4

https://www.supplychaindive.com/news/amazon-tents-logistics-delivery-footprint/552931/

How are AR and VR changing supply chains? by Abhilasha Satpathy, DCMME Center Graduate Student Assistant

AR improves the order picking process

By using smart glasses, employees can see exactly where items should fit on carts while they are picking orders. In addition to this, these smart lenses keep the picking lists in view of the order picker at all times, and shows them the most efficient route through the warehouse. This is a vast improvement over the commonly used process where order pickers use a piece of paper or hand scanner to hand select products and place them on carts.Not only does using AR reduce errors and increase order picking speed, it also reduces the need for intensive on the job training.

VR and AR for predictive modeling

Large retailers, and other distributors often have manufacturing facilities, distribution centers, and warehouses spread across the country and even have facilities overseas. At any given time, managers may not be on site. In spite of this, they still need to be on top of things. By using any number of virtual reality or augmented reality tools, managers can get a real time look at any site at any time to ensure that processes are running as planned. This is particularly important when issues have caused supply chain management disruptions.

VR can make the delivery process safer and more efficient

Delivery drivers are tasked with ensuring that products make it to stores, offices, homes, and distribution centers in a timely manner without damage done to products. Current processes include using navigation systems and manually checking cargo. With temperature controlled loads, things are even more complex. These solutions are often time consuming and distracting. The latter increases the chance for accidents. VR can be used to significantly improve this part of the supply chain process. For example, VR can be used to superimpose important information directly onto the windshield. Without glancing at a handheld device, drivers can see alternate routes, blocked roads and traffic snags. Even information about the load itself can be seen without the need to stop, climb into the back of the truck, and see what’s going on. VR even plays a role when drivers arrive at the point of delivery. Packages can be encoded with scannable images for drivers and unloaders. These can provide information such as package weight, contents and handling instructions. This means that before they even place their hands on a particular package the employee will know that a package is exceptionally heavy, fragile, requires a signature and is to be delivered at the south entrance.

Improved secured delivery options

When it is especially important to ensure that packages are delivered to a specific person, the current method is to verify identity and collect a signature. With customer cooperation and approval, VR can make secured delivery and identity verification even easier. A picture of the customer can be scanned into and stored in the company’s databases. Then, upon delivery, VR and facial recognition technology can be used to match the customer’s face with the picture in the database. As a result of this, it becomes easy to ensure that the recipient is the one intended to receive the delivery. This is a much more secure alternative to using picture IDs or signatures, both of which can be easily forged.

Questions:

  1. How is VR and AR making supply chain better?
  2. How is VR and AR improving secured delivery?
  3. How are AR and VR helping in predictive modeling?

Reference:

Arnold, A. (2018, March 24). How AR And VR Are Revolutionizing The Supply Chain. Retrieved from https://www.forbes.com/sites/andrewarnold/2018/01/29/how-ar-and-vr-are-revolutionizing-the-supply-chain/#630a572e4cbf

 

 

 

 

 

3D PRINTING – Eliminating Wastes and Reducing Carbon Footprint by Abhilasha Satpathy, DCMME Center Graduate Student Assistant

The economic advantages of metal additive manufacturing as an alternative to traditional methods are clear, but the reduced environmental impact may be even more important to the future of industry.

Shipping: An Enormous Carbon Footprint

The flow of raw materials into a manufacturing facility and finished goods out of it require enormous energy inputs allocated to shipping. Given that traditional manufacturing has been heavily reliant on fossil fuels since the Industrial Revolution, this process exacts a major toll on the environment. Together, the transportation sector accounts for over 30 percent of all U.S. emissions. Industrial transportation related to shipping undoubtedly comprises a major segment of this total.Complex, disjointed supply chains result in an end-use product that requires inputs to be shipped from hundreds of suppliers. Further, the completed product goes through multiple layers of distribution before it arrives in its buyer’s hands. 3D printing can’t fix all these problems, but it does have the potential to dramatically cut the number of links in the chain by allowing local, on-demand manufacturing of a huge variety of components. Without a doubt, 3D printing will eliminate millions of component shipping journeys in the coming decade.

Traditional Processes Waste Vital Resources

The largest segment of the metal parts fabrication industry is “subtractive” processes like CNC milling, in which material is cut away from a block to produce a final part.This brings us back to the key word, “subtractive.” The problem with this type of manufacturing is that any of the original block of metal that is cut away is waste. That wasted material represents additional resources that must be extracted from the Earth via potentially harmful mining practices.

Even worse, the final outcome for the scrap material itself involves one of two things:

  1. Additional shipping and processing to take advantage of whatever economic value the cast-off still has
  2. A trip to the local landfill, where industrial overcrowding is already a significant issue

Metal 3D printing, when economically viable, provides a nearly perfect solution to this problem. Because it’s an additive process, whereby material is layered onto itself in an exact pattern, there is virtually no waste associated. Only the metal that actually comprises the final component is used. The unused material can be recycled.This could mean the difference between 95% waste with CNC machining and < 1% waste using metal AM.

Toxic Byproducts are Common in Metal Manufacturing

Certain types of metal manufacturing, most notably CNC machining and metal injection molding, require the use of toxic substances as part of their process. The oils and lubricants needed to ensure CNC machines run properly are often dangerous to the environment. The finishing process for these parts can also make use of fluids that can be damaging if handled incorrectly. These must be handled carefully and disposed of properly.Needless to say, “properly” isn’t a standard to which all manufacturers worldwide are held. Some percentage of the harmful agents used in both CNC machining and metal injection molding will make it into the air, water, or soil that supports the community around a plant. It’s hard to quantify this, but the environmental impact is real.Standards for proper disposal of hazardous chemicals associated with conventional metal manufacturing can vary dramatically by world region.

Metal AM eliminates this concern entirely. The process simply doesn’t generate any toxic byproducts, which guarantees that air and water quality won’t be directly harmed.Conventionally made components can leave a much bigger carbon footprint than 3D printed parts.A less obvious environmental cost of traditional manufacturing lies in the efficiency of end-use products. Recent successes in metal 3D printing have changed what’s possible for fuel efficiency in a variety of places. The technology has enabled huge design improvements that shave off weight without compromising strength.

Lessening the Carbon Footprint Through AM-Enabled Design

3D printing allows for the manufacture of parts with complex internal geometries, often in ways that are impossible for conventional techniques to match. The upshot is that design changes that combine multiple parts into a single component can often be completed without sacrificing functionality–or feasibility. This accomplishes the goal of lowering cost and lead times by simplifying the manufacturing process, but it also comes with significant environmental advantages.

Additive Manufacturing Optimizes Designs & Efficiency

As the world marches toward an increasingly tenuous climate future, the costs of a suboptimal part made through traditional manufacturing must be considered right alongside the more tangible impacts described above. There are countless heavy or less-than-aerodynamic components in applications across every sector that could be improved significantly with the design freedom afforded by metal AM. In aggregate, the emissions reductions that are now feasible through projects like GE’s Advanced Turboprop engine would represent major improvement for humanity’s overall carbon footprint. Metal 3D printing doesn’t yet offer all the answers, but in a growing percentage of manufacturing situations, it’s a step in the right direction for our planet.

References:

3DEO. (n.d.). Environmental Impact of Additive Manufacturing. Retrieved from https://news.3deo.co/environmental-impact-of-additive-manufacturing

Questions:

  1. How is 3D printing reducing the carbon footprint?
  2. How is 3D printing reducing wastage?
  3. How is 3D printing optimizing designs and increasing efficiency?