Process Improvement / 4.0

Projects & References Technord has accumulated references in several fields

and has established a progressive roadmap for this type of innovation.

Process modelling in the extractive industry

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Technord and cell culture in biopharma

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Initiatives “4.0”, “IOT”, “Data Science”, “AI”, …

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Prediction of fermentation activity

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Success story for the Data Science department

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Cell Culture: Biological Modelling and Link with Monitoring Flows

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Production-Market Optimisation

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Scale-up separation process

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Optimisation of the moisture content of slag cement

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Predictive maintenance on a raw mill

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Performance Increase on a Production Line

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Artificial Intelligence for you ?

Being a full industrial integrator and therefore generating a lot of data for the customer, TECHNORD’s mission is to exploit this wealth of information to enable the customer to be more agile and get an extra percentage of yield improvement, or to solve a problem.

On the one hand, PI is fully aligned with our activities MES (Manufacturing Execution System) and IOT (Easysense platform and partnership with IBM).

On the other hand, PI meets the objectives of continuous improvement and operational excellence.

We analyse your data, we extract information that will help improve your operational excellence, we do modeling.

And we can integrate all this into your process, and connect this new tool for real-time prediction or decision support.

3 pillars for an IA project

What our your needs?

Data processing and modeling must be oriented to achieve an ambition or solve a problem. Potential topics must therefore be identified and prioritised.

Which data will be used?

The essence of artificial intelligence projects is the exploitation of data. A minimum of governance is needed to access it, to judge its quality and the necessary volume.

How to support your process improvement?

Last but not least: as with every innovation project, a decision-maker is needed to motivate the troops. The motivation and suggestions of the people involved will help develop the tool that will help them in the future!

This iterative process is effectively a simulation dialogue: data enables the simulation, the simulation stimulates ideas, then new data and ideas enable the simulation to be improved, etc.

Steps to a successful AI 4.0 project?

Start small, then expand your AI project

While good data governance and control are essential, starting with low-cost data exploitation can deliver swift results. Prioritizing efficiency over perfection will help to understand the innovation’s impact better.

We employ an incremental approach, which enables us to gather initial results and develop an agile roadmap for your business.

Take a few days to define your AI project in 3 steps

1. Conduct a feasibility study with guidance from our experts

Defining the project’s needs:

• What is the subject?
• Which individuals will be impacted by this project?

Defining the scope:

• Who are the contact persons?
• What types of data will be made available?
• Should the provided data be supplemented?
• Is data historization adequate?
• What are the process-specific characteristics: its dynamics, constraints, mode of operation?
• What type of modeling would be appropriate?

Anticipating and evaluating the project’s outcomes:

• What return on investment (ROI) should be expected?
• Which key performance indicators (KPIs) should be monitored?

2. Create an initial offline model

Then, we conduct a detailed analysis of historical data and engage with the client, resulting in the creation of an initial offline model. We maintain an ongoing discussion about the project’s results and its overall scope as it unfolds.

Reflect on the following questions with the model’s results in mind :

• How can decision-making be improved?
• What innovative work methods can you derive from the forecasts?
• What can be automated?

3. Definie your AI Project scope with our expertise

Lets translate the results to your needs into equations! The next steps depend on the initial results and your final goal:

• Continue to develop modeling in ‘offline’ mode, on more data or for an extended operating mode;
• Switch to real-time control: Use historic data and the simulator to build a controller. It will analyze the measurements in real-time to recognize the operating situation and provide the appropriate prediction;
• Suggest operating instructions to the operator to achieve the production target in terms of volume, quality, and emissions (open loop);
• Automatically influence process control, without operator validation. It is therefore a closed-loop operation, synonymous with Digital Twin in a ‘4.0’ context, or more simply Advanced Process Control.

A solution tailored to your activity

Depending on your position in the company, you may encounter diverse challenges and restrictions.

Our experts offer solutions for Production, R&D, Supply Chain and Maintenance.

• Production

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• R&D

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• Supply chain

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• Maintenance

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Production

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Production must deliver the volume defined in the schedule

• Maintain or increase output
• Reduce production costs as far as possible (targets/audit results)
• Manage non-conformities
• Reduce emissions as far as possible (Objective 0 Carbon)
• Adapting to market conditions (market forecasts, supplies, raw materials, etc.)
• Ensuring traceability of materials and products
• By supporting benchmarking of similar sites

Here are just a few examples of how you can boost the efficiency of your process.

• Real-time quality KPIs
• Breaking down data barriers
• Enhanced Control Strategy
• IA Outperform Spreadsheets
• Planning

Real-time quality KPIs

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Use a soft sensor model to provide real-time monitoring of KPIs, like quality metrics, rather than relying on the next lab sampling result.

Also, highlighting quality trends and future projections on a supervisory screen empowers decision support and process control to a higher level. This modeling approach can rectify biased measurement in real-time, mitigating known issues such as difficult calibration or rapid drift.

 

Breaking down data barriers

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Our data-driven approach gathers insights from diverse sources, including Scada, Quality, and Maintenance, to provide a holistic view of your process. But we don’t stop there; we break down data barriers to reveal a unified, cross-functional perspective that adds context to your product. While departments often hoard their data, we bridge the gaps, fostering collaboration. Our in-depth analysis across multiple databases identifies opportunities to boost OEE, from adjusting production rates to implementing new measurements and enhancing data governance

Enhanced Control Strategy

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Our modeling approach simplifies process dynamics :

• Refine parameters to address strong control constraints
• Introduce new control schemes when necessary thanks to simulations and data analysis

IA Outperform Spreadsheets

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Your production team might have developed its own calculation and analysis module, Technord is here to take it to the next level. Our powerful algorithms extract valuable insights from historical data, so you can expand your prediction capabilities for processes or create advanced recipe combinations.

Planning

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When scheduling becomes a puzzle, Data Science holds the key. Capitalize on historical order and delivery data and get automatic recommendations tailored to your business needs and synchronized with the Manufacturing Execution System (MES).

R&D

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R&D

Supply chain

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Supply Chain plays a crucial role in ensuring smooth supply flows to Production and customers::

• By coordinating available stocks effectively,
• By optimizing capacity volumes,
• By minimizing downtime and disruptions,
• By reducing shipping costs and carbon footprint,
• By benchmarking suppliers for excellence,
• By benchmarking distributors for top-notch service,
• By handling supply uncertainties, from equipment to materials,
• By anticipating market trends in the medium and long term,
• By fueling your corporate strategy.

As travel expenses soar and envirnmental concerns rise, logistics hurdles are becoming more intricate. We transform these hurdles into mathematical puzzles, offering realistic, industry-savvy solutions. Once validated, they become powerful suggestion tools, shaping tactical and strategic business scenarios (Sales & Operations – S&OP).”

• Logistics center
• S&OP

Logistics center

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When it comes to logistics centers, Data Science can help you :

• Identify breakdown causes and load disruptions by analyzing diverse data sources and established priority rules,
• Suggest rule modifications through a gradual evolution for step-by-step validation,
• Introduce fresh visualizations, displaying parameters or new context-driven KPIs derived from mathematical breakthrough.

S&OP

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Elevate Your S&OP with Data Science:

• Unify data from various sources—production capacities, variable costs, customs expenses, freight charges, sales forecasts, and beyond—to create a holistic resource visualization.
• Validate data reconciliation hypotheses and trial S&OP-conceived scenarios.
• Consolidate data to provide strategic insights.
• Devise scenarios to meet your market objectives.

Maintenance

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Smooth site and equipment operation, along with uninterrupted production and a secure work environment, rely on your maintenance unit. Here’ how they achieve it :

• By minimizing production downtime, whether planned or unexpected,
• By ensuring on-site personnel safety,
• By continuously monitoring equipment health through visual checks and data-driven anomaly detection,
• By analyzing energy consumption patterns,
• By establishing efficient calibration plans that are both preservative and resource-efficient.

Technord harness equipment and sensor data to help you :

• Provide context-driven dynamic operating, generating relevant and non-intrusive alarms
• Automatically assess equipment condition: by age, state of repair, potential longevity, and risks of recurring failures
• Predict measurement and equipment developments, facilitating predictive maintenance and stress-free planning to avoid surprises.
• Effectively ùanage sensor anomalies effectively by connecting those within the same context, shifting from individual measurements to correlation-based monitoring.
• Examine calibration records to establish optimal calibration strategies, guaranteeing safety margins while minimizing unnecessary calibrations.

Differentiation of TECHNORD

• TECHNORD’s AI team has a strong scientific and mathematical background. This allows us to apply a wide range of tools and concepts that we can detail in a presentation:

• We promote an unconditional transfer of the intellectual property of the projects to our clients. The tool is therefore fully owned by them.

• TECHNORD is an experienced integrator, with teams in most of the process layers :

• Our innovation strategy is well established with references that we will present to you.

Certifications Services certified to the current standards

We are certified at the highest level by the world’s leading manufacturers, thanks to our expertise and our involvement in countless projects in various and demanding industries.

News & agenda

News CANAL Z : interview de Philippe Foucart

The programme “Z Connected a news magazine of the economic and financial television channel Canal Z, is dedicated to the world of data in companies and the focus is on Technord! On this occasion, Vanessa Costanzo interviewed Philippe Foucart who presented Technord and the added value of Data Science in the improvement of production processes, …

Agenda Technord will be present at PharmaTech CosmeTech, Chartres, 31 May-2 June

PHARMATECH COSMETECH is a specialised exhibition dedicated to professionals in …

News Technord was featured in the April issue of the Pôlénergie Newsletter

Frédéric Vervoort, Head of Development Hauts de France and Robert …

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