Global Manufacturers Look to AI in Supply Chain

Manufacturing supply chains have undergone significant transformation in recent years, driven by the need to adapt to geopolitical instability and increasing global demand.

Whether it is an increase for new electric vehicles, more sustainable energy, or even just more streamlined operations throughout the product-to-consumer pipeline, every manufacturer has been impacted.

Throughout this volatility, five manufacturers stand out as paving the way through innovative supply chain strategies.

Schneider Electric: The "Self-Healing" Supply Chain

CSCO: Mourad Tamoud
Employee number: More than 80,000 staff members
Operations based: Operates across 160 factories and 75 distribution centres

Schneider Electric utilises a 'self-healing' supply chain platform which relies on adaptive machine learning, IoT and data in order to ensure real-time workflow optimisation. As it is constantly learning, it can readjust parameters of minimum order quantities, lead times and safety stock levels. 

Using IoT integration, its AI system has capabilities to improve financial and operational performance and offer predictive insights into business operations. This helps with scenario planning, strategy adjustments and greater visibility across the supply chain.

The data and machine learning helps businesses adapt to delays, shutdowns or event risks, meaning that a system can automatically identify alternatives in order to initiate replacements or change production schedules. This helps reduce monetary losses and mitigate risk much more effectively.

Schneider has seen a 10% overall inventory decrease through its 6-day reduction in day-in inventory. Products have been delivered at a greater speed – with a reduction of six days – and more than €100m (US$117.6m) has been generated in value.

Unilever: AI-Native "Virtual Factories"

CSCO: Willem Uijen
Operations: 280+ factories and 200+ warehouses

Unilever uses digital twins to create its 'virtual factories', using replications of production lines in a cloud-based environment in order to grow its operations. The company is investing in its staff and operations in an attempt to become 'AI native', through the embedding of machine learning across its global supply chain.

Moreover, Unilever is upskilling its staff as it aims to digitise operations, with more than 23,000 of its staff trained in AI in 2024. 

The company partnered with Microsoft in order to deploy its digital twins, utilising IoT and intelligent services within the Azure platform. Through this, the models utilise real-time data on temperature, cycle times and more in order to predict and optimise the manufacturing process. 

Unilever's Valinhos facility in Brazil saw immediate ROI from implementing digital twin technology, with energy cost savings of US$2.8m and a 1% to 3% increase in productivity. 

The technology is proving to create more efficient and productive supply chain operations, with cost savings to demonstrate the impact these virtual factories are having on the company.

"Our WEF Lighthouse sites reflect how our world-class operations are combining digital innovation with the passion and expertise of our people, enabling us to respond faster to demand," explains Willem Uijen, Chief Supply Chain and Operations Officer at Unilever.

Rolls-Royce: AI-Powered "Signature Analyser"

Chief Procurement and Supply Chain Officer: Martin Thomsen
Suppliers: More than 18,000 active suppliers
Annual spend: £7bn+ (US$9.5bn)

Rolls-Royce is revolutionising its operations with its 'signature analyser' method, utilising AI and machine learning in order to quickly identify defects. In order to improve productivity and cost savings, Rolls-Royce turned to Microsoft Cloud for Manufacturing for its digital transformation.

The analyser is part of its Smart Discovery and Intelligent Engine suits, detecting anomalies in engines. It utilises vibrations, thermal patterns and acoustic frequencies in order to predict component failures before they take place. 

The technology is able to filter out background noise in order to accurately spot disturbances. This has automated data science heavy lifting, with a significantly shortened investigation period. Rather than old systems which noticed the issue when it took place, the analyser can utilise trends, such as a change in sound or thermal pattern, before it becomes a wider issue. 

"We are investing heavily in modernising our systems and improving our design engineering. By embracing Microsoft AI and digital technologies, we will develop efficient and fully utilised smart factories, whilst enhancing our customer and employee experience," explains Kaveh Pourteymour, Group Chief Digital Information Officer at Rolls-Royce.

BMW Group: The "AIconic" Purchasing System

Senior VP of Strategy: Hendrik Lang
Suppliers: ~12,000 suppliers
Annual purchasing volume: ~€90bn (US$104bn)

The BMW Group utilises generative AI and its new intelligent multi-agent system BMW Group AIconic Agent in order to make stronger and more efficient decisions. It is a multi-agent AI ecosystem, working to automate global sourcing, meaning that human staff members can focus on the critical decision-making.

The system scans through historical information in order to gain consistency across BMW's supplier base so that it can create high quality request documents. Following the receipt of bids, the agents can perform deep dives in order to identify legal discrepancies, evaluate coverage and flag potential risks across the supply chain.

It examines global market trends, price fluctuations and geopolitical risks to enable leaders to make better purchasing decisions. Alconic is in place to eliminate manual labour so that BMW's workforce can be more supported throughout its operations. 

“At the BMW Group, we consider AI to be more than just a technological innovation. We see it as a key element of the digital transformation,” emphasises Hendrik Lang, Senior Vice President Strategy, Digitalisation and Sustainability, Purchasing and Supplier Network at BMW Group.

“Empowering our people to use AI technologies is our top priority."

PepsiCo: The "Omniverse" Distribution Center

SVP and CSCO: Karen Jordan
Employees: 10,000+
Manufacturing Plants: 61

In order to meet consumer demand and operate strategically amid ongoing turbulence, PepsiCo is partnering with NVIDIA and Siemens. In an aim to transform plant and supply chain operations, the company is applying advanced digital twin technology and AI. 

It is reshaping how facilities are simulated and tested in order to optimise its physical footprint. It is leveraging the NVIDIA Omniverse libraries in order to simulate upgrades to its facilities within the US before scaling globally. 

The technology allows it to co-design, validate and optimise facility layout before any physical builds take place, making it less costly but realistic alternative. It means that PepsiCo can trial what works for its expansion before spending large sums of money on something which may not make a significant difference.

"The scale and complexity of PepsiCo’s business, from farm to shelf, is massive—and we are embedding AI throughout our operations to better meet the increasing demands of our consumers and customers,” says Ramon Laguarta, Chairman and CEO of PepsiCo.

“Our work with Siemens and NVIDIA will help accelerate our continued journey of becoming a future-fit company, operating with agility and foresight.”