Will RFID Technology Really Change the Supply Chain?

What-is-RFID

RFID technology has made it possible for organizations to better track consumer goods, improve security and track employee attendance. An RFID tag can include specific information about the object being scanned, and it can be updated as needed to include additional information. An additional benefit of RFID tags is the ability to scan tags from a great distance, making them an ideal option for warehousing, security and supply chain applications.

How RFID Tags Work

An RFID tag sends and receives information from a tag to a device that can interpret the data. The tag doesn’t have to be directly in the line of sight of a reader to work properly. Tags must simply be within the transmission area of a reader. RFID tags can be classified as active, passive and semi-active. Active and semi-active tags are powered by batteries or use an external power source. This makes them more expensive, but it also increases the transmission range. Passive tags don’t require a battery to run, and are often thought to be more resilient. The power for a passive RFID chip comes from the reader’s electromagnet. The range of passive readers is typically limited to around 30 meters, while active readers can extend up to 300 meters.

The Types of RFID

There are essentially three types of RFID technology available on the market – low-frequency, high-frequency and ultra-high-frequency. Each option has its own positives and negatives.

Low-frequency(LF) implementation uses low range frequencies around 135 KHz for tracking animals, livestock and auto-immobilization systems. These low frequency options make it easier to work in harsh environments and can even work under water. However, there are limits to this type of technology, namely, you can’t read multiple tags at the same time and the read rate is slower.

High-frequency (HF) implementations are usually used in consumer retail environments, and use a frequency of 13.56 MHz. Garments typically use these types of tags, which can be used to track inventory, and set off alarms if the tag leaves the store without being deactivated or removed. Ticket payments, pharmaceuticals and even passports may also include this technology to make reading information simple and efficient.

Ultra-high-frequency (UHF) implementations are generally used to work in fast moving operations. For example, they can be used to track pallets moving across an assembly line or for applications that demand real-time, quick scanning technologies. The military often uses this type of RFID tag to maintain and track its assets, since the technology can be implemented directly into a circuit board.

New Innovations in RFID Technology

There are a variety of innovative uses for RFID technology that are hitting the consumer market. Coffee cups may automatically start up a computer, or open files on your PC when you arrive at work in the morning. Smart tiles can be used to program smart phones and other devices to complete entire programs, such as starting a playlist, or turning on a set of lights in a home. Refrigerators can help manage your inventory and give you a quick grocery list or alert you when your stock is low.

Automated shipping systems can also use RFID technology to automatically pick and select items for shipment. This can greatly reduce the cost of labor associated with warehouses that ship pharmaceuticals, retail products and other companies that have complex distribution systems. These complex systems have an RF picking system, conveyors, carousels and pick-to-light systems that make collecting and shipping packages much more efficient.

The main uses for RFID users in the consumer technology field aim to make finding and locating information easier. Many self-checkout machines in grocery stores use a form of RFID. This makes it possible to scan products quickly and pay for items without having to go to a cashier. Electronic tags or displays can provide information about products, and get easily updated as information changes. Trolley readers can be used to scan products and find out the price of an item with taxes and other fees. Shelf tags are used in stores to quickly update the prices of several products, just by walking through the aisle with an updated transmitter. Additionally, different prices can be applied to the same item with an expiration data that is coming up soon, or for an item that has been damaged in some way.

In 2014, the RFID Journal awarded Bechtel with a Best RFID Implementation Award. The award was given for a new, groundbreaking use of technology. The company uses thousands of active RFID tags to control construction materials and shipping systems for three natural gas projects. This proves that RFID technology can be used in large-scale projects with thousands of variables. It pushes the envelope of what is available, and can be an essential tool for companies that want to deliver projects on time.

RFID-applications

Hazards of RFID Technology

While RFID technology has the ability to transmit a large amount of specific information in a quick manner, it isn’t without its risks. Thieves can use readers to get information on RFID cards and tags without having to come in contact with the actual card. This threat can be neutralized by taking care to keep cards in special holders that prevent unauthorized access, and by encrypting information on the cards.

CubiScan Wins 2015 MHI Innovation Award

March 25, 2015

CubiScan® by Quantronix, along with the CubiScan® 25, was honored as the winner of the 2015 MHI Innovation Award as an existing product [in this case, using existing technology developed previously for the CubiScan 125]. The CubiScan 25 dimensioning and weighing system was designed to measure odd-shaped parts, eaches, apparel, and any other irregular piece less than 18″.

Learn more at CubiScan.com

How Ecommerce and Big Data are Changing Everything

In the past, excessive data volume posed a storage dilemma that made discarding data pretty much the only solution for private business. Garbage-in-garbage-out was the prevailing mindset. Then technology reached a point where it became cheaper to store and analyze data than to discard it. At that point the big data industry was born.

Welcome to the future. It’s a brave new world; one in which analysts can now predict things like fluctuations in the Dow Jones Industrial Average, using statistical models that analyze, you guessed it, Big Data. Big data is big news in pretty much every corner of the economy. Some of its major advocates are even predicting such things as disease prevention and reduction of government bureaucracy. The possibilities are pretty captivating. But for now lets talk about the more day-to-day uses of big data.

Ecommerce

We’ll get to the definition of the term ‘big data’ in a second but for now, what the usefulness of big data boils down to essentially, is that elements of business logistics that used to be a lot of mysticism and guesswork — too nebulous for most people to even think about — are now reduced to simple analytical decision making processes. Even though there’s still some debate on the best definition of the phrase ‘big data,’ from a general, semantic standpoint, we can at least think of it as a catch-all term that describes any data set too large to process using conventional desktop methods like spreadsheets.

A Cyberspace Odyssey …

Early in the year 2001, tech-industry analyst Doug Laney published what is now considered the mainstream definition of big data. It’s really more like the key elements of big data that help businesses definite the term for themselves case-by-case. In any case, Laney’s breakdown is known definitively as the three Vs: volume, velocity and variety. As mentioned previously, the definition of big data varies, industry-by-industry, depending on which of those elements takes precedence and how that information is applied. Narrowing down the answer to those questions depends on the specific goals businesses want big data to help them accomplish, whether it’s to increase revenue, reduce costs, optimize transit time, increase efficiency at various levels, or whatever else. So let’s get a little more in-depth with the three-V’s to start the conversation off and then we’ll move on to a few ways e-commerce companies are leveraging all those stockpiles of information.

Volume

Many factors contributed to the increase in data volume. Transaction-based data stored through the years. Unstructured data streaming in from social media. Increasing amounts of sensor and machine-to-machine data being collected. With decreasing storage costs, other issues emerged, including how to determine relevance within large data volumes and how to use analytics to create value from relevant data.

Velocity

Data streams in now at unprecedented speeds and must be digested quickly. RFID tags, sensors and smart metering drive the need to deal with torrents of data in nearly-real time. Reactions executed quickly enough to deal with data velocity poses a challenge for most organizations.

Variety

Data today comes in all types of formats. Structured, numeric data in traditional databases, information created from line-of-business applications, unstructured text documents, email, video, audio, stock ticker data and financial transactions. Managing, merging and governing different varieties of data is something many organizations still grapple with.

Big Data

So what are e-commerce companies doing to utilize big data?

1. Optimizing Shipping

Shipping companies make their living managing transit times, and so by the associative property, e-commerce companies need to as well. Think of it this way: transit time equates to time spent with engines running fuel burning, and man-hours accumulating. Those are all costs that eventually trickle down to shippers themselves. But really those are just the traditional lookback data that help companies determine where inefficiencies may exist. It forms a small part of the big data picture. Other non-traditional data relevant to the equation might include weather and traffic delays, port strikes, and/or unexpected repairs on those endlessly running engines. Data indicating trajectories within those systems may come from GPS devices, RFID tags, and traffic management systems, and possibly social media monitoring. Those sources are what businesses can compare against lookback data to identify patterns then forecast potential problems, take measures to avoid them, and presumably improve their bottom line. Learn more about shipping systems.

2. Supply Chain Management

According to an IndustryWeek report 97 percent of executives claim some understanding of how big data will improve their supply chain, while only 17 percent claim to have implemented it. On its face those statistics may seem like a lot of talk around the latest trendy buzzword, but all that talk is leading to understanding, and understanding is slowly leading to action. Nearly 40 percent of the same executives surveyed claim to have initiatives underway to implement big data analytics into their supply chain. The same IndustryWeek report emphasized the effectiveness over enterprise-wide adoption of big data as opposed to the processed-focused approach. What’s interesting is that those who have adopted the enterprise-wide approach report marked improvements at the process level. For example, 61 percent of those who have adopted enterprise-wide big data analytics have shortened their order-to-delivery cycle times.

3. Business Tracking

Amazon is using their own big data analytics tool, EMR, based on the open-source Hadoop platform to track expenses, income, and human resource information. Considering that some of Amazon’s warehouses are larger in both square area and employee numbers than some small towns in the U.S., that’s no small task. It’s a big data task. UPS is using big data to track up to the minutes speeds and direction of over 46,000 delivery vehicles. The company is reporting millions of gallons of fuel saved, and hundreds of millions of miles shaved off daily delivery routes after optimizing shipping systems, delivery routes, and configuring drivers’ pick-ups and drop-offs, all using big data.

4. Tracking Customer Preferences

Restaurant chains are using big data to track customer preferences in all sorts of categories. McDonald’s for example, is compiling trend-analytics to optimize drive-thru experience based on types of customers passing through, menu design, and information provided on the menu. The hope is that spotting trends in demand will inform measures to improve efficiency. But informing businesses what to do is not the only application to customer preference tracking. It also helps them know what not to do. According to an article posted on Wired, we can all thank big data of nipping that whole ‘bacon makes everything better,’ trend in the bud. It may seem a little silly, but it was big data that informed restaurateurs to put bacon back on sandwiches and take it off dessert items, and out of beverages.

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