17th May 2018
PP Control & Automation, with comments from Chief Technical and Information Officer, Ian Knight, featured in The Sunday Times.
When Ian Knight heard about the government’s plan to boost apprenticeships, he couldn’t believe his luck. The 43-year-old was desperate to inject some new blood into Walsall-based PP Control & Automation, where he oversees staff training.
Things have not gone to plan, though. The new apprentices Knight has hired are spending more time in the classroom than on the job. It’s not just Brexit: this government is failing business at every turn.
One of the UK’s leading strategic manufacturing specialists is tapping into the UK’s unprecedented investment in upgrading the electricity grid.
As Britain accelerates investment in grid infrastructure, protection and control capacity could become a critical delivery constraint.
The appointment of a new Prime Minister inevitably brings renewed debate about the direction of the UK economy and what it could mean for business.
Ian Knight, Chief Information Officer at PP Control & Automation (PP C&A) challenges the prevailing, often vague narrative around AI adoption and reframes the conversation around a more practical starting point: operational constraints.
Artificial intelligence is no longer a distant concept for manufacturers. It is already being explored across quotation, production planning, engineering, quality, supply chain and customer service functions. Yet, for many organisations, the gap between experimentation and meaningful operational impact remains difficult to close.
A leading aquaculture specialist – that is changing the way fish are vaccinated safely – has signed a major manufacturing deal.
On paper, defined discipline-specific suppliers can look organised. However, every additional supplier introduces another handoff, and every handoff creates another point where time, quality, communication and accountability can be lost.
Very rarely does growth not surface because an OEM lacks ambition. Shortcomings arise because operating models built to support such ambition don’t evolve quickly enough.
