While you will find a relentless justification for the need to apply science to manufacturing management in these articles, it would be rather naive to think that just looking after the mathematics will solve all of the challenges. Digital transformation is complex and is enabled through people. People need leadership, particularly in organisations, and if you are to be successful at delivering your vision of digital manufacturing, there needs to be someone at the front who knows how to enact change.
Pilot schemes are an effective way of introducing potentially disruptive practices to an organisation. It’s of vital importance to indicate the success at a small scale so that there is evidence that the change works in your organisation’s culture.
The mathematics of analytics is not always difficult, and simple tools like spreadsheets can take the brunt of the daily workload. Training staff to apply this thinking to their activities can take time, but gets better with practice on your digital manufacturing journey.
One effective way of ensuring that staff in the pilot become engaged is to make sure that either the measures of the improvement can be explicitly linked to their efforts, or that their efforts are directly measured.
In the same way that an SPC chart can show a machinist when the tool has lost its edge, individual’s performance on activities can be measured as above, within, or below some control limits. This data is an essential ingredient of a successful digital manufacturing ecosystem.
Reporting such results enables staff to direct their efforts to the most pressing priorities, while also engendering a culture of continuous improvement.
The linking of production activity to monitoring of manufacturing objectives helps develop a culture whereby operations are of interest, and studied by all staff, rather than leaving it all to the production planning department.