Artificial Intelligence is being implemented by companies all around the world; one particular sector that will see massive benefits is Supply Chain Management for Electronic Components. Properly utilized, AI can provide automated oversight into manufacturing and production lines, create strategies to assess and adapt to new challenges or unforeseen incidents, and reduce the need for human engagement in menial, repetitive tasks.
For decades now, we’ve been teased about how Artificial Intelligence (AI) will invariably change our way of life. From iconic literature such as Isaac Asimov’s I, Robot to Hollywood blockbusters 2001: A Space Odyssey, Terminator, and The Matrix, science fiction has long touted the inevitable emergence of AI into mainstream society.
And ever so gradually, it’s been happening.
Nowadays, Siri and Alexa have become common, household names. Nearly every new car in America is programmed with onboard navigation features that learn our preferred routes and travel habits. We obsess over the latest Fitbits and iWatches, and a plethora of other fashionable smart devices to aid in our everyday health, jobs, and happiness.
You may be shocked to learn AI is already a reality; today, AI is being implemented by companies all around the world, albeit in a limited capacity. And yet, the days of Skynet remain in the distant horizon — a promise of what’s to come. One day. Maybe.
Or perhaps, sooner than you think.
What is Artificial Intelligence?
Quite simply, AI is machine-based intelligence.
AI can be completely independent of human interaction, such as a robot working on a manufacturing production line. Alternatively, it can be a software program designed to perform complex data analysis tasks and generate real-time reports for a human operator to interpret and modify.
Today, AI is being implemented in practically every industry, within every part of the process, from the procurement of raw materials to the engagement of consumers purchasing the end product. While some aspects of the process are easier for AI to adopt than others (e.g., production line AI vs. fully-automated customer service), supply chain management (SCM) appears to be a tailored fit for AI integration.
Due to the need for real-time analyses and processing, coupled with the sheer quantity and complexity of data, the world of SCM is primed for AI to lend a virtual hand.
Below is a quick list of ten ways AI is, can, and will improve the world of supply chain management in the electronic components sector:
- Smart Traffic Systems
AI can monitor, assess, and predict traffic congestions before they occur. AI systems such as Rapid Flow Technologies’ SURTRAC optimizes signal timings at specific junctions, allowing for real-time traffic coordination throughout fluctuating road conditions.
Predictive algorithms can also be devised by AI systems to alert and advise drivers on the best driving routes.
- Self-Healing Supply Chains
In many ways the best example of how AI can benefit SCM is operating within a closed loop system, i.e., a process with no need for human input. Algorithms determined by an AI construct can be used to detect patterns in historical data, whereupon the same AI can use those insights to make mathematically accurate predictions to correct erroneous data in real-time. The supply chain then becomes a continuously self-healing system, no human oversight needed.
- Continuous Monitoring
AI systems also allow you to monitor vast amounts of data from numerous sources in real-time, around the clock, from anywhere in the world. These sources can be as diverse as social media trends, news stories, and weather forecasts, all of which could have a very real impact on demand, and your ability to meet that demand.
- Automated Planning Agent
AI software can provide an alert planning agent that’s able to differentiate between low impact incidences and critical ones. The former can be dealt with by software, along with a detailed report of what’s detected and any actions taken. For critical issues that require human engagement, alerts can be sent out to relevant parties for decisive action. The parameters of what the AI will construe as “low impact” vs “critical” can be set by an operator for a hands-off approach, and of course can be reviewed or altered depending on evolving need.
- Machine Learning
Machine learning is the term generally given to the part of AI that’s concerned with data analytics; more specifically, machine learning refers to the algorithms designed to detect patterns in data and act accordingly, as discussed in the self-healing process above. In their report, Smartening up with Artificial Intelligence, McKinsey & Company predict that by adopting endless loop techniques and software, forecasting errors will be reduced by half. The impact of machine learning is a massive improvement in product availability which in turn will result, according to the same McKinsey report, in up to a two thirds reduction in lost and missed sales.
- Optimized Algorithms on the Shop Floor
An added benefit to machine learning is any data collected through real-time monitoring can be used to objectively assess a particular machine’s impact and contribution during a specific production schedule. This data can then be used to streamline the manufacturing process, making it more efficient, as well as recommending optimal combinations of machines for new production runs.
- Better Customer Satisfaction
With the implementation of AI strategy into SCM, companies can expect to see increases in productivity and output as a result of smarter inventory practices, more precise replenishment planning, and increasingly accurate demand forecasts. As the process from manufacturing to end product becomes more tapered and focused, companies can choose to pass these savings to customers in the form of reduced prices and shorter restock time.
Chatbots are becoming an increasingly regular feature on company websites and applications. With Chatbots, businesses are able to defer repetitive, low impact tasks to AI software rather than spending resources on hiring and training individuals. Today, suitable Chatbot tasks differ from company to company, but they’re commonly used for the receiving, filing, and documentation of invoices, as well as for placing purchase orders and engaging in low-level communication with end users.
- Improved Existing Human Workforce
Additionally, AI can benefit human team members by giving less experienced planners and analysts tools (and parameters) to enable appropriate decision making and recommendations. AI-supported training software can drastically reduce learning curves, allowing professional growth to be tailored to the individual.
- Autonomous Vehicles
In the not-so-distant future, autonomous vehicles are expected to have a significant impact on supply chain logistics. Driving legislation determining the number of hours a driver can be behind the wheel varies from country to country, but there is (understandably) a cap in regards to safety. Driverless vehicles can open up the possibility of drastically reducing logistical transport times, saving time and money, and thus passing the savings onto consumers down the line.
For purposes of brevity, we’ve limited our list to ten examples, but there are plenty of other ways AI can and will be influencing supply chain management in the near future. Did we miss a crucial one? Aching to add to our list? Let us know in the comments below!