Engineering Magazine – June 2019

30 JUNE 2019 ENGINEERING

The future of smart

manufacturing

Smart factories are rapidly becoming the future of manufacturing, offering a new

level of efficiency and productivity to those investing in them. Simon Kampa

makes the point that Industry 4.0, combined with increasingly sophisticated

analytics, is playing a huge role in driving the smart factory movement

M

anufacturing executives and

engineers no longer see a

factory as a mass of machinery

operating as part of one or more

individual production lines. Instead,

they see an interconnected network of

moving parts, something more akin to

a living and breathing organism, that can

be fine-tuned to optimize performance.

New technologies such as big data,

prognostics, artificial intelligence (A.I.)

and the cloud ensure that those who

manage and maintain manufacturing

environments can get on the front

foot and proactively manage these

environments, with relatively low levels

of investment.

The potential of this new

era of responsive machinery is

expansive, enabling a higher level

of communication, transparency

and therefore, yield, between all

stakeholders; Business owners can

predict and manage the failures of their

machinery and, with a new call for

servitization, suppliers can minimize

their maintenance costs.

The rise of predictive

maintenance

For decades, condition monitoring

and predictive maintenance have

been a reality for the few and a

dream for the majority. The cost and

complexity of gathering and analysing

sufficient data to drive tangible results

has limited predictive maintenance to

the defence and aerospace sectors.

However, the rise of the Industry

4.0, where production assets are

connected to the internet and able to

communicate, combined with A.I. and

advanced analytics from companies

such as Senseye, has opened up the

world of predictive maintenance to a

much wider range of industries and

use cases.

Until recently, gathering the data

required to inform conditioning

monitoring activities has been a laborious

manual process requiring specialist

expertise. The growing use of self-

sensing machines that record their own

vital statistics and relay them for analysis

over the internet, and the ability to

retrofit older assets with smart sensors

to do much the same, allows data to

SOFTWARE

Simon Kampa