PC-MAR22-PG18-19.1_Layout 1 07/03/2022 13:55 Page 18


INDUSTRY 4.0/IIOT ‘PURE IMAGINATION’ BECOMES REALITY


Keith Thornhill and Saad Waqar, both from Siemens UK & Ireland, believe now is the time to unlock the opportunities of digitalisation


L


ast year marked the 50th anniversary of the iconic 1971 film Willy Wonka & the Chocolate Factory. As the first screen adaptation of Roald Dahl’s book, it tells the story of Charlie Bucket’s life-changing visit to the famous confectionery manufacturing plant, where production of an array of sweets and treats was entirely automated, save for the minor interventions of the Oompa-Loompas. It was also the setting for a classic Hollywood computer cameo from Siemens involving an overconfident engineer who fails to demonstrate “the greatest miracle of the machine age” by using a supercomputer to reveal the locations of the final golden tickets. The fictional computer, which refuses the engineer’s request to find the golden tickets because it “would be cheating”, was actually based on a Siemens 4004, a real system commonly deployed in industrial settings for its data processing capabilities. And while the real-life Siemens computer didn’t have the processing to uncover the whereabouts of the last Wonka bars, the scene hinted at the aspirations for data analysis, AI and machine learning technology. Fast forward to present day and automation, intelligent processes and almost endless storage space in the cloud have laid the foundations for data collection and analysis capable of birthing breakthroughs, generating insights and paving the way for successful new strategies to take shape across the wider food and beverage industry. Today’s factories are becoming huge data centres with great potential for collecting valuable insights on any area of factory operations. Industry 4.0 has paved the way for smart data-driven production plants. However, despite the massive potential of the wealth of facts and figures now available to food and beverage manufacturers, Keith Thornhill, believes the sector hasn’t laid firm enough foundations to unlock the opportunities. He said: “As it stands, I’m not too sure there are many companies out there with Wonka-like end-to-end connectivity as


18 MARCH 2022 | PROCESS & CONTROL


Keith Thornhill (left), head of Food and Beverage for


Siemens UK & Ireland, and Saad Waqar (below) business development manager for Digitalisation, Siemens UK & Ireland


aqar (below)


their vision. They know technology is going to make a difference, of course, but they only see it in terms of how that is going to benefit their next delivery, rather than how it will affect them in five to ten years’ time. New data reporting technologies are a particularly good place to start to


discover where change is needed.” Recent research by Siemens in the UK and Ireland found that 81% of food and beverage manufacturers are exploring more ways of capturing, managing and analysing production line data. But despite high uptake and good intentions, just 38% of manufacturers agreed that they had ‘somewhat’ achieved data maturity.


“Without the data to help measure operations, it is often difficult – or impossible – to know where further investment is needed,” Thornhill explained. “Until manufacturers have an accurate real-time view of production, they have no benchmark of production efficiency and therefore a limited idea of the performance benefits and scale of improvement that can be gained. Expertise is needed to help turn data into actionable intelligence.” He continued: “As is the case with most short shelf-life foods, producing baked goods at volume is a mixture of controlled process and complex science, with many variables having an impact on performance. Tracking and analysing production data is a big step forward in reducing waste and improving efficiency.


“Conditions need to be controlled to optimise quality and throughput. And parameters, such as humidity and heat, as well as supply chain variability, need to be monitored as part of root cause analysis. Uncontrolled variability is normally the reason


Recent research from Siemens Financial Services showed that the window of opportunity to gain competitive advantages through digitalisation investments is narrowing, with a ‘tipping point’ of around 5 years, after which manufacturers will be playing catch-up


why production lines stop unintentionally. “By tracking the necessary processes through technology and connecting these data sources to central dashboards for visualisation, manufacturers can spot exactly where their faults and inefficiencies lie and act quickly to prevent failures or improve operations.”


But it is not just reducing downtime that can save costs. “Through the collection of data and use of simulation technology, one of my bakery customers discovered that it could save over £1m a year by improving the control of its chilling process to reduce energy and potentially increase capacity,” Thornhill added. Streamlining where possible is the answer. Working out where seconds can be shaved off production schedules or where energy usage can be reduced is vital for manufacturers that need to produce perishable products quickly. One example where a technological intervention boosted efficiency and cut costs was a project for Kinnerton, a major UK confectionery manufacturer. From initial chocolate mould filling to product cooling and packaging, Siemens simplified Kinnerton’s production line process via a Totally Integrated Automation solution. It meant streams of different data - from simple conveyor belts to sophisticated ‘pick and place’ packing robots - all linked to different manufacturing processes were connected centrally, giving Kinnerton a real-time picture of the whole production process. The project, at Kinnerton’s factory in Norfolk, succeeded in boosting productivity on one line by 15%, meaning that the technology quickly led to increased output and sales. So what can you do once you’ve got to grips with all that data?


Aside from using data to pinpoint manufacturing inefficiencies, there are some trailblazing examples of food and drink


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66