By Insight Editor / 7 Dec 2023 / Topics: Data and AI Intelligent edge Digital transformation
Add inflationary pressures and the frequency and severity of natural disasters to the mix, and it’s a wonder our supply chain still works at all.
According to Coupa, more than 80% of organizations experienced at least one significant disruption to their supply chain last year, with 50% experiencing three or more disruptions.
And those disruptions cost businesses dearly. Research conducted by Economist Impact found they lost an average of 6–10% in annual revenue — on top of reputational damage suffered when customers couldn’t find what they needed on store shelves.
Threats to the supply chain can ebb and flow over time. But one thing is certain: resilience and agility — the ability to bounce back from supply chain disruptions and quickly adapt to new changes — is essential to help your business stay competitive and profitable.
Yet to be resilient and agile, you need the right tools. Innovative technology can help you predict supply chain issues in advance and adjust your operations accordingly — so you can optimize production while consistently maintaining product quality.
How can you rise above supply chain disruptions and stay competitive? Let’s explore some of the tools and solutions available from Insight that can help.
When supply chain disruptions happen, you need to know about them right away, not a week or month later.
That’s where real-time insights come into play. Real-time insights allow you to collect, analyze and interpret large amounts of data as it’s being generated. This up-to-the-minute information enables you to immediately respond to changing market conditions, customer demands and operational challenges based on instantaneous data.
A few of the latest technologies Insight offers that deliver real-time insights include:
Real-time insights can also be used for things like predictive maintenance, which uses AI technology to predict when equipment is going to fail. This allows you to perform maintenance before a breakdown happens, which reduces downtime and extends the life of your equipment.
Additionally, these insights can be leveraged in dynamic scheduling: the ability to optimize production schedules in real time. Analyzing data on customer demand, inventory levels and production capacity helps you immediately adjust production schedules, reducing lead time and improving customer satisfaction.
Overall, real-time insights can provide significant benefits to your business by allowing it to operate more efficiently, improve quality and respond to quickly changing market conditions.
Predictive analytics and machine learning are ushering in a manufacturing revolution that’s taking the world by storm. A true global phenomenon, these machine-based processes empower businesses to become dramatically more efficient in their processes, use resources wisely and increase productivity.
With a wide array of choices, some examples of predictive analytics include demand forecasting, which uses AI, historical data and statistical models to forecast future demands and outcomes. It’s almost like a crystal ball that helps you read changes in the market and customer behaviors in real time. You can even pose specific questions, like, “Are there any new supply chain disruptions on the horizon I should know about?” or “How much of this product will I need each month for the rest of the year?”
Machine learning takes things a step further by automating the prediction process. Instead of simply analyzing data and producing insights, machine learning algorithms can be trained to make decisions and take action based on that data.
For example, a machine learning algorithm can be trained to predict when a machine will fail. These predictive maintenance models can even be built with added precision to deliver a higher level of accuracy. So instead of only predicting when a machine will fail, precision analytics can identify which components are likely to fail and when — giving you time to schedule preventative maintenance before the failure happens.
Additional predictive models like quality control can help you anticipate when a product might become defective, while maintenance scheduling can help predict when machines are likely to need repair.
To help reduce your carbon footprint, predictive energy management can analyze energy usage to predict future consumption and make conservation recommendations, while supply chain risk management can help identify potential disruptions in the availability of raw materials and finished goods.
One everyday way predictive analytics can be used to help business is by analyzing the weather to forecast when a big storm is going to hit. Based on this prediction, a manufacturer can adjust shipments of raw materials and finished goods to avoid the weather disruption.
Predictive analytics models can be scaled up or down to fit any size of the business or manufacturing process. Whether your need is for a single line or a global model that runs across multiple factories, they can be used to automate work in real time. This makes it possible to respond to changing conditions, like automatically adjusting merchandise stock levels based on real-time customer demand.
Overall, predictive analytics and machine learning have become key tools in helping manufacturers streamline operations and stay competitive in an increasingly data-driven world.
What was once considered a science fiction, Terminator-esque idea, has recently grown into a multi-billion-dollar industry.
Continuous advancements in AI, machine learning and sensor technologies are driving the incorporation of robotics and workflow automation into manufacturing at breakneck speed.
Together, these technologies dramatically increase efficiency, reduce on-the-job accidents, and deliver round-the-clock production that can dramatically increase productivity and profits.
Any industry that makes something — or moves something — at scale has a potential use for industrial robots.
Some of the most popular in the manufacturing market today are collaborative robots called “cobots.”
Cobots work alongside humans in industries like the auto, aerospace, eCommerce sectors and handle mundane, repetitive and dangerous tasks that can frequently cause worker fatigue, injuries and manufacturing inefficiencies.
Cobots are exceptionally helpful at performing tasks like:
Many companies that have incorporated robotics and automation into their manufacturing say the benefits are worth the investment. Those benefits include:
With such a long list of benefits, it’s easy to see why demand for robotics and workflow automation is booming. According to the International Federation of Robotics, 517,385 new industrial robots were installed in factories around the world in 2021, bringing the current stock of operational robots to 3.5 million units globally — a new record.
By 2032, the global industrial robotics market is expected to hit $142.8 billion — nearly triple its value of $48.5 billion in 2022, reflecting a CAGR growth rate above 11.4%.
In today’s fast-paced and technology-driven landscape, the success of your business is directly linked to the equipment you choose. The latest automated technologies can offer real-time visibility into your operations, providing valuable insights that facilitate improved productivity, risk minimization and a competitive edge.
By partnering with Insight, you’ll have access to cutting-edge solutions and an experienced team to help you navigate the complexities of evolving manufacturing technologies. With Insight as your trusted technology partner, you can confidently stay ahead of the curve and be equipped to rise above supply chain interruptions.
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