Dynamic Manufacturing Dashboard Software – The Tools of the Transparent Factory

Most recently viewing methods have become a critical factor when data is being utilized by an organization.  Mobility is the norm in modern business and the team’s ability to stay connected to the data via mobile analytics has become key.  The use of smartphones and tablets has skyrocketed, with the addition of people utilizing their own devices in a work environment.  This means any system absolutely must be visible through smartphone and tablet based applications.

Knowledge is power, and the power to select the information needed and how that is delivered should be put in the hands of those using the data.  It would be easy to let the IT department design and deliver various dashboards to those that need them, assessing requirements, driving metrics and providing a one size fits many solution.  This is firstly a burdensome task for any IT team, all of which are at least stretched, and in most cases overworked.  But perhaps more importantly it does not deliver the kind of tailored information that each individual might want to see to allow them to better discharge their responsibilities.  Putting the layout of the shop floor production dashboard into the hands of the person who will derive use from it is the only way to empower them, ensuring they have exactly what they want, when and where they need it. The more practical and most successful dynamic manufacturing solutions occur when the power to design the dashboard is delivered to the user.  The least attractive and agile solution occurs when the users relinquish responsibility for the configuration and assign it to the integrator or vendor.  Flexibility is also essential at the initial stage.  Dashboards and configurations should be allowed to develop and evolve.  The data needed by an individual today may not be the same as that required tomorrow.  What’s more not everyone will get their manufacturing analytics dashboard specification right first time. They will want to adapt as they go and as they see what data points assist them the most.  They may drop less relevant material, just as they may find data they didn’t expect to need essential.

Configurable manufacturing dashboards are an essential feature of a successful system and are at the heart of the transparent factory.  This needs to be as simple as dragging and dropping elements into a design space, telling each element where to derive its data and exactly how to display it.  This needs to happen without input from the IT team and certainly without any coding, SQL or IT knowledge.  Without this simplicity and flexibility the system will not keep pace with the enterprise and the teams requirements for differing and changing data presentation.

Not all dynamic manufacturing dashboards need to be truly real-time.  Some will only need to be refreshed once an hour, once a day, or even once a week.  Factories typically display their monthly quality and production charts on a wall or a notice board on the factory floor, usually printed out and pinned up.  A transparent factory will likely have screens at these locations with the data displayed on dashboards updating on a regular basis with longer-term analytics rather than real-time information included.  This is essentially a hybrid between a live dashboard and a report, providing information that is refreshed at a predetermined rate.

Reports and analytics should have the same flexibility, being entirely and simply configured by a user with no coding, SQL or IT skills.  Otherwise every new report or minor change to an existing report will be expensive and will create delay.  A reporting system that enables data mining via a graphical interface and data interrogation by visually traversing the graphs and data sets is the only means to meet the ever-changing analytics demands of a truly transparent factory.  Of course, the ability to write SQL if needed should be present but cannot be the only means.  These flexible reports are hugely valuable when teams meet to resolve a specific issue, and the transparency means they can mine deeper into specific data when required.

As well as those reports that are generated on demand, the system should have the ability to provide automated scheduled reports.  Many of those in the enterprise who need or are able to make use of data do not have the time or the inclination to go into a system and generate a report.  Systems should auto-generate reports on a regular basis and distribute that report to the parties who will obtain value from it.  These auto generated reports might be for a single shift, daily, weekly or even monthly, highlighting key data as well as trends that allow better decisions to be made.  Some users might even play an entirely passive role in the ecosystem while benefiting from the reported data.

Again this user configuration and flexibility must apply regardless of the display device.  Most important the same data and same customizable nature should apply to mobile devices.  Being able to build a manufacturing quality dashboard for the smartphone or tablet as well as the desktop, or shop-floor based display is essential to allow the on-the-move user to access the data they need, particularly when emergency analysis and reaction is required.  As mentioned above, auto-generated reports should be made available on mobile devices and notifications sent when necessary.

As well as considering a mobile workforce, it is also important to consider a data ecosystem that operates beyond a single facility and a single geography.  With businesses and supply chains operating on an increasingly global basis, reporting tools must have the means for groups of staff to interrogate and traverse large data sets across multiple facilities in multiple geographies, and perhaps through multiple vendors when a partially or fully outsourced model is deployed.

Collaborative data mining can be extremely valuable in a team meeting where the root cause of problem is not fully understood.  Flat static reports are rarely conclusive in themselves and the ability to drill into data in real-time can quickly reveal causes inevitably leading to solutions.