generalised usage of data

How can the use of data in the factory be generalised?

Industrial companies still fail to make widespread use of data in their plant. It is 2022 and this statement is still true. Why industrial companies are failing? Main obstacles and key drivers to scale-up data use in the plant…

energy performance industry

Energy performance in process manufacturing industry

The year 2022 is marked by tensions on energy supply. At the same time, new measures are being implemented to force players to reduce their CO2 emissions. Some of the causes of these tensions may be temporary, but most are structural and will persist…


Industry data driven operational teams

Data and digitization are transforming deeply how operational teams are working, and we must say, it is a great opportunity for them as well as for their organisation.

vignette productivite

Industrial productivity: how to deliver more from assets?

Productivity is a key challenge for industrials. Producing more from existing assets has several positive impacts on profitability. But how can it be improved?

site adisseo

Group-wide digital transformation: Adisseo’s experience

Through the implementation of OIAnalytics on Adisseo’s sites, discover the key success factors of a successful group-wide digital transformation.

data performance

Achieving sustainable performance with data

How can a global approach to data improve your performance in the long term? Move from data to action and improve your performance.

facteur influent process

Process influencing factors identification: wich strategy?

Discover the objectives of identifying the factors influencing a production process, our approach and the approach we recommend.

Enterprise Manufacturing Intelligence

Enterprise manufacturing intelligence 2.0: EMI

Enterprise Manufacturing Intelligence: solutions to enhance the value of information, focused on the uses and autonomy of users around data.


A collaboration tool to improve productivity: Toshiba’s experience

Now implemented on the toner production line, the OIAnalytics solution provides TOSHIBA Dieppe’s teams with a collaborative tool to improve productivity and industrial performance.

Remote support for industrial performance

Facilitating interactions between teams: how does digitalization make it possible to dematerialize support for industrial performance?

Using data science in the plant

Contributions of Data Science and Machine Learning in the field. Discover the many opportunities to gain performance in the plant by overcoming the limitations of these approaches.

Digitizing industrial pilots: Eramet’s experience

Quickly and autonomously set up the collection of data from industrial pilots and simplify their processing : Eramet testimony.

Data Lake in industry

Store data over time and process it to better manage activities and improve performance. What about a global Data-Lake?

Industrial processes: defining your data analysis strategy

The keys to effectively manage a project to enhance the value of your data in order to meet your industrial challenges.

smart data

Processes, data and people: where does smart data fit in your organization

How the technological mutations around data will allow people to free themselves from worthless tasks to focus on their expertise and know-how.