Supply chain management with AI
On average, businesses estimate they spend 55 hours per week doing manual processes and checks. Could this be avoided?
Here, Jonathan Wilkins, Marketing Director industrial parts supplier EU Automation, explains the potential of artificial intelligence (AI) in supply chain management.
These trivial, but necessary, tasks equate to 6,500 work-hours in the working year, some of which could be saved by implementing AI and automation. However, these financial issues represent just one part of the complex supply chain. Could wider challenges, such as logistics and distribution also benefit from the AI treatment?
With volumes of data growing at an unprecedented rate, computers are capable of parsing data in a contextual manner, providing useful insight to an operator — without them doing any of the legwork. Big data technologies are also capable of analysing market trends, integrating with enterprise systems and triggering automated actions based on the data it collects.
Build AI readiness
Businesses must have large data sets of deep granularity for effective AI to take place. Granularity is used to characterize the scale or level of detail in a set of data, of which AI is highly dependent on. The greater the granularity, the deeper the level of detail across the data. Whether AI implementation is in the forthcoming plans or not, it's a good idea to ensure data collection and storage are geared for high granularity.
Boosting granularity may mean increasing the frequency of data readings, refining the precision of such recordings or even placing sensors in new places to measure new variables. For example, if a flow meter is currently measuring the flow rate of a liquid in litres per minute, changing this recording to millilitres per minute may provide more insightful data. Ultimately, even if a business is not AI-ready today, improving granularity will lay the foundation for when AI inevitably becomes a competitive differentiator.
Target a specific problem
Have one business goal in mind at the beginning. Focusing efforts and resources on a single problem means a significant pain point can be tackled effectively, with relatively low risk compared to a complete overhaul of processes. By selecting a discrete project, initial successes can be built upon and lessons can be learned and then applied to other areas in the supply chain.
Equipment supply planning
Supply chain planning is a crucial activity, using intelligent work tools to build concrete plans for things that could go wrong. For example, using data from past equipment and current machine performance, AI can accurately predict when a part will need to be replaced in order to maintain the optimal running of a plant. This is critical, particularly for old legacy equipment that is now obsolete, as lead times to find the part from an obsolete parts supplier will vary.
As the complex web of production and distribution are opened up to the benefits of AI, the supply chain will have a bigger economic impact than any other application of the technology. In fact, Mckinsey estimates firms will derive between USD$1.3bn and $2.1bn a year in economic value by implementing AI into the supply chains.
But remember — for businesses just starting out with this technology, the focus should remain on building data granularity and choosing a specific issue to overcome with this technology.
This article was contributed by Jonathan Wilkins, Marketing Director, EU Automation
Intelliwave SiteSense boosts APTIM material tracking
“We’ve been engaged with the APTIM team since early 2019 providing SiteSense, our mobile construction SaaS solution, for their maintenance and construction projects, allowing them to track materials and equipment, and manage inventory.
We have been working with the APTIM team to standardize material tracking processes and procedures, ultimately with the goal of reducing the amount of time spent looking for materials. Industry studies show that better management of materials can lead to a 16% increase in craft labour productivity.
Everyone knows construction is one of the oldest industries but it’s one of the least tech driven comparatively. About 95% of Engineering and Construction data captured goes unused, 13% of working hours are spent looking for data and around 30% of companies have applications that don’t integrate.
With APTIM, we’re looking at early risk detection, through predictive analysis and forecasting of material constraints, integrating with the ecosystem of software platforms and reporting on real-time data with a ‘field-first’ focus – through initiatives like the Digital Foreman. The APTIM team has seen great wins in the field, utilising bar-code technology, to check in thousands of material items quickly compared to manual methods.
There are three key areas when it comes to successful Materials Management in the software sector – culture, technology, and vendor engagement.
Given the state of world affairs, access to data needs to be off site via the cloud to support remote working conditions, providing a ‘single source of truth’ accessed by many parties; the tech sector is always growing, so companies need faster and more reliable access to this cloud data; digital supply chain initiatives engage vendors a lot earlier in the process to drive collaboration and to engage with their clients, which gives more assurance as there is more emphasis on automating data capture.
It’s been a challenging period with the pandemic, particularly for the supply chain. Look what happened in the Suez Canal – things can suddenly impact material costs and availability, and you really have to be more efficient to survive and succeed. Virtual system access can solve some issues and you need to look at data access in a wider net.
Solving problems comes down to better visibility, and proactively solving issues with vendors and enabling construction teams to execute their work. The biggest cause of delays is not being able to provide teams with what they need.
On average 2% of materials are lost or re-ordered, which only factors in the material cost, what is not captured is the duplicated effort of procurement, vendor and shipping costs, all of which have an environmental impact.
As things start to stabilise, APTIM continues to utilize SiteSense to boost efficiencies and solve productivity issues proactively. Integrating with 3D/4D modelling is just the precipice of what we can do. Access to data can help you firm up bids to win work, to make better cost estimates, and AI and ML are the next phase, providing an eco-system of tools.
A key focus for Intelliwave and APTIM is to increase the availability of data, whether it’s creating a data warehouse for visualisations or increasing integrations to provide additional value. We want to move to a more of an enterprise usage phase – up to now it’s been project based – so more people can access data in real time.