Jan 29, 2021

Unlocking the value of supply chain process through AI

AI
MachineLearning
IoT
Automation
Jim Chappell, Global Head of A...
6 min
Jim Chappell, Global Head of AI and Advanced Analytics at AVEVA looks at the benefits of artificial intelligence within complex businesses
Jim Chappell, Global Head of AI and Advanced Analytics at AVEVA looks at the benefits of artificial intelligence within complex businesses...

Over the past four decades, much of manufacturing production worldwide has been organised in what has become known as Global Value Chains (GVCs). COVID-19 has struck at the core of global value chain hub regions, including China, Europe and the US.

Now, as production comes back up to speed, companies are scrambling for a means of monitoring the inbound flow of product, to figure out how it can be received, stored and shipped at a time when demand for all but the most critical items has ceased. This has prompted many businesses to review their current supply chain processes and to evaluate how they might build in resilience ahead of any future disruption.

Digitalisation is essential for industry in this current climate, both to increase margins and operational performance in good times and to adapt in the bad. AI has reached a key juncture where the real-world benefits are instantly recognisable. 

Understanding where AI boosts existing processes  

In the industrial sector, AI application is supported by the increasing adoption of devices and sensors connected through the Internet of Things (IoT). Production machines, vehicles, or devices carried by human workers generate enormous amounts of data. AI enables the use of such data for highly value-adding tasks such as predictive maintenance or performance optimisation at unprecedented levels of accuracy. Hence, the combination of IoT and AI has begun the next wave of performance improvements, especially in the industrial sector. 

Furthering this automation, AI uses the historical IoT data to analyse trends which can help in streamlining and improving the supply chain process through cutting-edge solutions such as AI-driven operations scheduling. This provides recommendations to humans as to the optimal scheduling sequence, substantially reducing error and inefficiencies.Further, this AI learns as it goes and tailors its guidance to particular situations, gaining intelligence the more it runs. In addition, AI-driven robotic process automation removes the human element from repetitive tasks in varying levels of complexity, thus furthering increases in efficiency and accuracy. Through integrated workflows, much of the supply chain process can be intelligently automated. These types of AI-driven capabilities have the potential to redefine the business supply chain process. In certain industries such as oil and gas, these types of operational gains are more important than ever in today’s climate.

Early adopters of AI have deployed these technologies on-premises, in the cloud, at the edge, and through many types of hybrid architectures. AI itself is not one thing but comprised of several technology types, including neural networks, deep learning, natural language processing, computer vision, unsupervised machine learning, supervised machine learning, reinforcement learning, transfer learning, and others. These various types of AI are applied in different ways throughout the industrial world to create targeted solutions provided as descriptive, predictive, prescriptive, and prognostic analytics. 

Overcoming the fear of automation

Beyond deciding where and how to best employ AI, an organisational culture open to the collaboration of humans and machines is crucial for getting the most out of AI. Trust is among the key mindsets and attitudes of successful human-machine collaboration. 

Here are some practical steps to consider if a business is looking to explore the implementation of 

Artificial Intelligence or Machine learning capability into their business process: 

  1. Leverage AI to gain significantly more value out of existing industrial software: SCADA (an acronym for Supervisory Control and Data Acquisition generally refers to industrial control systems) and other types of control systems have become standard practice in most industrial facilities. Real-time and historical data is typically used for trending, reporting, and HMI visualisation. AI allows companies to get much more value and insight from this historian data through state-of-the-art technologies such as multi-variate machine learning and deep learning. By integrating software infused with AI into existing industrial IT infrastructures, businesses can greatly amplify the value and ROI by detecting and solving operational and maintenance issues before they become larger problems that often result in unplanned downtime. This alone can increase uptime by 10% annually, resulting in substantial avoided costs and efficiency gains. 
  2. Allow AI to integrate into the core of the supply chain to take advantage of cutting edge capabilities: AI-driven operational scheduling and work process automation can eliminate mistakes and allow industrial companies to get the most out of the resources they have available. Supply chain success is critical to overall business success, and an increase in efficiency can often be the difference between turning a profit or not. AI provides incredible value in this area, and businesses shouldn’t be afraid to leverage its power as an integral part of their supply chain process.
  3. Use the cloud to ease the implementation of AI, allowing companies to scale: Artificial Intelligence is fast becoming the brains behind the cloud. Consequently, companies can quickly deploy and access a variety of industrial software capabilities that are driven by various types of AI technology. The cloud is the delivery mechanism, and SaaS is the commercial model; however, AI drives much of the value gained. Now more than ever before, AI is becoming more easily accessible and more cost-effective to deploy into industrial environments. 
  4. Bridge the gap between AI and humans: In order to glean maximum value from AI, companies must ensure that they bridge the gap between AI and human understanding. A significant portion of the workforce today is somewhat distrustful or fearful of AI. It is critical that companies do everything they can to ensure that the benefits from AI-infused software are translated into the vernacular of the targeted worker. The benefits provided by AI must be put in context, be useful and actionable. If this does not happen, then much of the value of AI is wasted.
  5. Be open to continued innovation and change: AI capabilities continue to evolve and improve. Software will become more intelligent through combinations of AI capabilities in order to achieve more sophisticated machine-based thought and reasoning. Amid these changes, companies can reap more and more benefits through deeper insight into cost vs risk decisions, an improved understanding of business processes and associated efficiencies, and better forecasts of future events. By continuing to plan for and incorporate change, companies can take advantage of ever-improving AI capabilities and insight.

Time to reflect and evolve

Businesses now need to be incredibly agile to manage the costs of turning down production, followed by the working capital constraints to then rebuild production levels as economies recover. We are also seeing a period of distrust and disinformation while global supply chains are disrupted, data is key to traceability and provenance ensuring that drugs and food come from authentic sources. Better visibility allows us to understand where resources such as food and pharmaceuticals are and how we can get energy efficiently to those who need it.

Digital transformation stands to provide an immediate and compelling competitive advantage for those quick to adopt – and to demonstrate provenance. Businesses require intelligent software to address industrial pain points for value creation, productivity improvement, insight discovery, risk management, and cost optimisation. AI is a key differentiator and a propelling force behind improvements in the supply chain.

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Jul 31, 2021

RAIN RFID, IoT and AI are key to a proactive supply chain

Supplychain
Technology
RFID
IoT
Jill West, Vice President Stra...
4 min
RAIN RFID, IoT and AI are key to shifting supply chain’s technology adoption from reactive to proactive in the post-pandemic era

Across supply chains around the world, we have seen leading companies rely heavily on technologies like AI and IoT during the pandemic. These digital solutions have enabled businesses to accurately capture and ultimately use their own first-party data to drive efficiencies and protect increasingly fragile bottom lines.

However, what is less commonly known is the increasing role of RAIN RFID technology in supporting IoT solutions. By using RAIN RFID to capture item data and then feed that data into AI systems, businesses can identify inefficiencies within the supply chain and make informed decisions.

What is RAIN RFID?

In short, RAIN RFID is a powerful IoT technology that enables itemised data collection. By applying small, battery-free tags to items, organisations can identify, locate, and authenticate each of those items, scanning up to thousands of items simultaneously with a variety of devices, including hand-held, fixed and wearable readers.

RAIN RFID solutions dramatically improve the operational capabilities of an organisation by ensuring they have exactly the right items, in the right quantities, at the right locations, at the right time. During the pandemic, RAIN RFID solutions have been key to limiting disruptions in retail and manufacturing supply chains, most notably by increasing inventory and asset visibility and improving the management and flow of goods. 

Three ways RAIN RFID helps solve supply chain concerns

RAIN RFID is used to streamline processes, maintain real-time inventory, increase productivity, and help manage labour shortages. We see three key ways RAIN RFID helps solve supply chain concerns:

  1. Automate shipment verification: Today, significant labour is required for multiple, manual barcode scans during the shipment process. RAIN RFID tags can be read automatically without a direct line of sight, erasing the need for workers to pause, locate a barcode, and scan it. By using RAIN RFID, supply chain leaders can automate their shipment verification process and improve warehouse efficiencies by up to 25%.
  2. Deliver real-time visibility: Retail Systems Research says that 76% of supply chain survey respondents reported that real-time inventory visibility was their leading focus for improving performance. When supply chain managers lack information about the status of assets and shipments moving into and out of warehouses, confidence and productivity suffer. By using RAIN RFID, supply chain leaders gain real-time visibility into an item’s identity, usage, and location. With this information, they can quickly find inventory and assets, and reduce the cost of asset investments. 
  3. Improve order accuracy: Today, companies rely on redundant manual checks to verify that the right cartons are loaded onto the correct pallets. By using RAIN RFID, supply chain leaders can automate pallet build verification to streamline the process and increase order accuracy. In fact, a recent study by Auburn University found that RAIN RFID can help an organisation achieve up to 100% order accuracy, eliminating claims costs and unhappy customers.  

RAIN RFID can increase value of AI-powered analytics

In today’s AI-driven, rapid decision-making business environment, RAIN RFID is uniquely capable of making systems more effective. This is because it provides item identifiers for tracking and locating billions of items, from clothing to food, pharmaceuticals, tools, packages, pallets, and more.

It also works without line-of-sight, providing visibility into places and processes not previously available. The data provided by a RAIN RFID system can give AI-powered solutions the ability to see individual items throughout the supply chain, understand how the entire supply chain is functioning and identify which areas can be improved. 

As companies accelerate digital transformation, we expect to see a rise in interconnected data as investments into new technologies and IoT surge. But as the volume of real-time and accurate data about the movement of goods rises, so too do the demands on operations teams to make sound business decisions quickly and with confidence, often using AI-powered systems that thrive on improved data to make better decisions. 

As an example, over the past several years, Delta Airlines transformed its customer experience by investing in technology including real-time RAIN RFID bag tracking and automatic check-in via the Fly Delta mobile app. Delta is now leveraging this set of investments in their implementation of an AI-driven platform that analyses millions of operational data points, from luggage movement to aircraft positions to flight crew restrictions to airport conditions. This system simulates operating challenges and creates hypothetical scenarios that help Delta’s professionals make critical operational decisions that improve the overall customer experience.  

Looking forward

The need to drive digital transformation rapidly during the pandemic has made supply chain and logistics professionals increasingly tech savvy. As we prepare for a post-pandemic era, companies’ increased know-how and awareness of solutions like RAIN RFID, IoT and AI will play a key role in evolving the industry’s approach to solving supply chain issues from reactive to proactive, setting them up for future success.

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