Strategy 4.0 - Valmex - Made

Strategy 4.0 – Valmex

Introduction

Valmex is a world leader in the supply of components for the domestic heating sector.

The problem

Valmex wants to embark on a digital transformation journey in order to achieve a higher level of digital maturity. To do so, the company must first:

Understanding methodologies to implement in your processes.

Understanding methodologies to implement in your processes.

Identify the most important innovation projects.

By doing so, the company will receive a strategy that will serve as a guideline for transferring Industry 4.0 concepts into the company.

The solution

“Industry 4.0 Strategy” is the tool that MADE provides to manufacturing companies to accompany them on their digital transformation journey. In particular, this service involves identifying, in accordance with the objectives and specific characteristics of each company, a plan for adopting digital technologies and strategic skills suitable for ensuring the evolution towards Industry 4.0, both in terms of process efficiency and effectiveness.

Technologies

Digital Transformation

Roadmap 4.0

Strategy 4.0

Desired impacts

Assessment of the digital maturity level of each business process and function (product engineering and design, production management, quality management, logistics management, maintenance management, supply chain management).

Analysis of the strengths and weaknesses of each process investigated.

Identification of opportunities for improvement that can guide the company’s digital journey.

Assignment and planning of projects for the introduction of digital solutions based on business support.

Identification and definition of five appropriate innovation projects to lead the company towards an Industry 4.0 paradigm.

Launch of two innovation projects on the following topics: cyber security and production scheduling optimization.

Benefits for the company

The strategic plan is broken down into a tactical-operational plan.

The activities, skills, timeframes, and resources required by the company to undertake the various innovation projects identified are identified.

Identification of a cross-functional approach necessary to guide the company in addressing critical issues (and therefore improvement projects) with significant collaboration between departments.

Related insghts

Fundings

Courses

Projects

Technologies

All fundings

AI-MATTERS:

Experience artificial intelligence solutions

Contenuto on-demand Base Online Big Data Analytics

Training pill – Big Data & Analytics

Tools for analyzing, managing, and selecting vendor-independent Big Data solutions.

Contenuto on-demand Base Online Cyber security industriale

Training pill – Cybersecurity industry 4.0

Complete course on IT and industrial security, with theory, models, and real-life examples.

On-demand training Basic Online

Training pill – Introduction to Artificial Intelligence for Industry 4.0

Course on AI, machine learning, neural networks, data, evaluation, and industrial applications.

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Logistics

The digital transformation of logistics and production enables intelligent control of the supply chain and production processes. Thanks to IoT and smart sensors, it is possible to collect real-time data to optimize transportation routes and inventory management. Cloud platforms and predictive analytics support dynamic planning, reducing operational costs. The process Digital Twin allows for the simulation of production scenarios and the identification of inefficiencies before they occur. This integrated approach enables more flexible, responsive production that can quickly adapt to market demands.

Smart Product and Process

The Intelligent Product and Process enables a new industrial paradigm, where products and machinery are connected and capable of exchanging information in real-time. Thanks to IoT and Smart Connected Products, companies can collect operational data, monitor product conditions, and improve predictive maintenance. Advanced process monitoring allows for the optimization of production and the reduction of waste, while servitization transforms business models, shifting from product sales to the provision of services based on actual use. These technologies enhance operational efficiency and promote more flexible and sustainable production.

Artificial Intelligence

Artificial Intelligence optimizes every stage of production, reducing costs and improving operational quality. In quality control, artificial vision systems and machine learning detect defects before they impact production. Predictive maintenance analyzes critical parameters to reduce machine downtime. Autonomous guided systems manage material handling with optimized routes. Advanced industrial data analysis improves planning, energy efficiency, and supply chain management. Indeed, AI for operator assistance provides support with intelligent chatbots and augmented reality, enhancing safety and efficiency.

Connected Infrastructure

The Connected Infrastructure is the cornerstone of industrial digital transformation, enabling the collection and utilization of data from machines, sensors, and software. The digital backbone ensures a continuous flow of information between departments and plants, allowing for predictive analytics and faster decision-making. The use of Big Data Analytics transforms large volumes of data into actionable insights to improve quality, energy efficiency, and productivity. Industrial cybersecurity protects sensitive data from cyber threats, ensuring operational continuity. With this digital infrastructure, companies can reduce waste, anticipate failures, and make processes more sustainable.

Product and process development

Product and Process development can be optimized through the combined use of advanced digital technologies, which improve design and industrialization. The digital twin allows for the creation of a virtual replica of the product or production process to analyze performance and identify issues before physical implementation. Virtual commissioning enables the digital testing of production systems, reducing startup times and the risk of malfunctions. Advanced simulation and virtual reality enhance design and testing, allowing for more accurate planning. With PLM (Product Lifecycle Management), it is possible to manage the entire product lifecycle in an integrated manner, optimizing resources and reducing waste.

Quality

Quality 4.0 represents an evolution in industrial quality control, leveraging advanced digital technologies. Computer vision systems and AI monitor every stage of production, detecting anomalies before they become critical defects. Integration with IoT sensors ensures complete product traceability throughout the supply chain, enhancing the safety and reliability of supplies. Techniques such as X-ray tomography and other non-destructive inspection methods allow for the verification of internal quality without compromising component integrity. This approach reduces waste and rework, optimizing production processes.

Smart Maintenance

Smart Maintenance represents an innovative approach to industrial plant management, leveraging digital tools to prevent failures and reduce operational costs. Predictive maintenance uses IoT sensors and artificial intelligence algorithms to monitor machine conditions and anticipate potential anomalies. Augmented Reality (AR) supports operators with detailed visual instructions, making repairs faster and more accurate. Maintenance planning, based on data analysis and predictive models, optimizes resource usage and reduces downtime. These technologies improve operational continuity and enhance plant safety.

Smart Production

Modern industry requires flexible and optimized production systems. Smart Manufacturing integrates advanced digital solutions to improve performance and efficiency. Cobots support operators in repetitive tasks, reducing errors and fatigue. 3D printing enables on-demand production and material optimization. Digital machine monitoring, thanks to IoT and AI, allows anomalies to be identified and consistent quality to be guaranteed. The digital twin of the process allows production scenarios to be simulated and informed decisions to be made. Thanks to these tools, production becomes more responsive, efficient, and sustainable.