AI for manufacturing companies
Producing smarter with AI: from buzzword to business value
Artificial Intelligence is no longer an experimental technology. Since 2022, we have seen a clear acceleration in the adoption of AI within manufacturing companies. Front runners are turning pilots into concrete, real world applications. At the same time, many organizations feel the pressure to “do something” with AI, while often not knowing where to start or what value it can actually deliver.
Cadran Analytics helps manufacturing companies take that first step. With one foot firmly in ERP and deep industry expertise, we translate AI technology into scalable solutions with a measurable impact on the bottom line.
Recognizable pain points in manufacturing
The challenges in manufacturing are concrete and felt on a daily basis. Supply chain disruptions make demand and lead times unpredictable, while labor shortages and rising energy costs increase pressure on organizations. At the same time, sustainability ambitions continue to grow.
IT often provides insufficient support. Data is spread across multiple systems: ERP holds orders and inventory, shop floor software records operational processes, and machines generate performance and maintenance signals. The result is a lack of overview. Are you sure you are selling the right products, holding the right inventory levels, and producing on time?
AI helps organizations regain control through three value drivers: more efficient processes and automation, new insights from data, and new forms of collaboration and business models. By identifying patterns, predicting trends, and supporting decision-making, data becomes a tool for steering rather than an obstacle.
Why AI is relevant for manufacturing
- Efficiency – AI helps operations run more smoothly. Smarter planning and reduced downtime lead to faster delivery times and lower costs.
- Insights from data – AI makes fragmented data from ERP, MES (Manufacturing Execution Systems), and OT (Operational Technology) usable for better decisions. You gain predictive insights and scenarios around demand, capacity, inventory, and risks. This increases delivery reliability, reduces emergency shipments, and shows where adjustments are needed.
- New opportunities – AI opens the door to new ways of working, such as more flexible production or smarter purchasing. This makes your organization more agile and strengthens profitability.
AI for manufacturing: challenges and solutions
| Efficiency (Operational Excellence) | Insights from data (new insights) | New models & strategy (servitization, agility) | |
|---|---|---|---|
|
Supply chain
Disruptions in the supply chain |
AI scenarios and dynamic scheduling make production and transport quickly adjustable. | End-to-end scenarios balance cost, service, and CO₂ and make impact visible. Gain insight into bottlenecks across the chain and simulate the impact of shocks. | Plan to switch fast; AI selects the best option based on timing, cost, and reliability. Offer customers AI-driven alternative products when your own products are unavailable. |
|
Workforce
Skills shortages and an ageing workforce |
Smarter deployment of scarce staff through better planning. | Create a knowledge base that can be searched using AI. | Offer customers more self-service through chatbots. |
|
Energy & CO₂
Energy prices and decarbonisation |
Shift energy-intensive work to cheaper hours (“load shifting”) and plan with energy awareness to reduce costs. | Identify “energy leaks” in your production processes. | Move production to hours with lower prices or lower CO₂ intensity. |
|
Data
Scaling the data foundation and digitalisation |
Label, classify, and aggregate your data using AI. | Make clear who uses which data and for what purpose, and identify gaps. | Propose new products to customers with comparable specifications and better margins. |
|
Finance
Working capital and cash conversion cycle |
Predict optimal inventory levels. | Predict late payers and proactively follow up. | Vendor-managed inventory (VMI/consignment): suppliers remain owners until use; less own inventory while service levels stay high. |
Why choose an AI solution from Cadran Analytics?
- Proven experience in the manufacturing industry, from discrete assembly to process manufacturing.
- A unique combination of ERP expertise and AI technology, ensuring models truly fit your operational reality.
- Specialization in Databricks, MLflow, and Microsoft Azure for a secure and future ready data platform.
- A multidisciplinary team of data engineers, data scientists, and BI consultants working closely with operators, planners, and quality teams.
- A strong focus on solutions that deliver immediate value within your processes, not on experiments without a solid business case.
Jelle Huisman
Managing Partner
Are you ready to use AI for smart improvements in your production environment?
In a demo, we show where AI can already deliver value in your production environment today and how you can scale this in a controlled way.
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