DispoX provides the environment to collaboratively evaluate the impact of changes on existing factory before the project team can commit to any investment.
data and model
DispoX work environment includes an enterprise data lake, which is a repository of all equipment data collected from factories or public domain. It also includes all factory models that has been built or tested. They are stored in a secure and comprehensive cloud infrastructure. The user selects the Analytic Twin Model of the factory to be used to evaluate planned changes. He then selects the set of equipment data to be applied to the model. By default, the company’s standard equipment database is selected.
The upgraded factory model is built from an existing model. Changes of model are made from DispoX graphic user interface, where DispoX tracks predictive factory performance as it is being drawn to immediately signal and suggest solutions, when it is unable to meet the production target before the change is even completed thereby saving the project team plenty of time.
TO ANALYSE, PREDICT AND GET RECOMMENDATIONS
Once the model is upgraded, Engineering or Continuous Improvement teams in charge of the project can evaluate the impact of changes options on the production: product mix, product volume, control policy, equipment capacity, equipment availability. At this stage, the tools available are the same as the ones for Factory Design. Also, as for Factory Design, input assumption and results can be easily shared with stakeholders for collaborative work and effective decision making. This process enables the project team to get it right first time.
Huge saving can also be brought by Industrial Engineering team as they can leverage on the vast amount of DispoX equipment database to benchmark equipment performance within one or several factories to identify improvement opportunities throughout factories.