The Critical Path to Manufacturing Efficiency
The connected technologies that underpin Industry 4.0 promise to transform manufacturing with real-time insight into any aspects of operation that risk degrading finely-tuned processes. But there is a problem – the way organisations are able to respond to that insight. Where is the prioritisation to guarantee that it is the most critical alerts that are attended to in order to minimise any business or employee impact? The information about the type of fault? Or the ability to track response? The dated paging and mobile systems in use by many companies are simply not enabling companies to achieve the promised improvements in operational efficiency.
Real-time information is of no value if it is not used effectively. It is therefore essential to consider the critical path; to assess how the information provided by devices and sensors to deliver vital alerts could and should be used to facilitate the quickest response possible. It is the analysis of this path, the understanding of the steps needed to be taken, and the ability to design the most successful workflows that leverage smart communications solutions that will improve both processes and employee safety.
Klaus Allion, Managing Director at ANT Telecom, questions the value of adding information without actionable intelligence.
The latest budget was full of incentives for manufacturing companies to increase their investment in capital stock – in a bid to address the UK’s lack of productivity, under investment in equipment over the past decade and extended reliance on cheap labour. And to be fair, the opportunities for investment are immense given the current level of innovation and change. From Artificial Intelligence (AI) to robotics, the Internet of Things (IoT) to Industry 4.0, few manufacturing companies could be in any doubt that there are many ways to leverage innovation to drive productivity improvements.
But organisations cannot afford to look at innovative technologies in isolation. IoT, for example, is all about providing real-time alerts from sensors or devices to inform operations – from highlighting temperature variations that could affect product quality, to revealing a drop in valve performance or raising the alarm of a lone worker accident. Fantastic – what company wouldn’t want an early warning of potential problems that could affect a finely honed manufacturing process or employee safety?
But what happens next? How does the company respond to these alerts? Information is brilliant but it is only of true business value if actioned intelligently to achieve measurable improvements within operations. The availability of real-time alerts in the event not only of machine failure, but machine degradation that could affect product quality is just the start. It is the way the company responds to the alert that makes the real difference. What is the process for ensuring the right people are informed and able to rapidly remedy the issue? How are alerts prioritised? Right now, this is where far too many manufacturing processes fall down.
Of course, manufacturing plants have been collecting alert information from machines for years – long before IoT exploded the devices and sensors available. Supervisory control and data acquisition (SCADA) systems for remote monitoring and control are a standard component of any operating environment, providing a single view of equipment performance on a large screen in a control room. More recently, these systems have gone mobile, offering operators and maintenance engineers the chance to view the red, amber, green alerts on a tablet while on, or away from, the factory floor.
That’s great. But the way in which organisations respond to these alerts is still, in the main, archaic. A red alert could prompt a generic page message to which any number of individuals may or may not respond. Alternatively, an operator viewing the red alert on the SCADA screen has to call the engineering team leader who will access a control panel to understand the true nature of the problem and only then identify and contact a team member to resolve the issue.
Reliance on such dated communication models is clearly inadequate - especially given the cost, maturity and robustness of alternatives. An intelligent smartphone based communication system can enable a far more interactive response - if companies reconsider the critical path.
Step by Step
Direct integration between a communication system and a control panel, for example, provides immediate information about the nature of the fault. Smart workflow then ensures the system automatically contacts the most relevant team, such as electrical engineering, eliminating a number of time consuming manual steps. Once the designated team member has received the smartphone based notification, they can confirm their attendance and, critically, provide updates on the repair resolution.
This approach can be extended to that mass of often overwhelming SCADA data – replacing ad hoc decision making with automated, workflow based processes that effectively prioritise and communicate requirements to engineering teams. Rather than give the engineers the same mass of overwhelming red, amber, green information on a small tablet, just show the critical alert. There are huge risks that a red dot will be missed amid a mass of other coloured dots – if it is a priority, make it clear: a massive red dot that stands out from the rest will ensure the engineer recognises the priority and responds.
There is, of course, no one perfect critical path – every organisation will have different demands, priorities and skills required to respond to production line glitches. But there are huge efficiency gains that can be achieved simply by leveraging expertise to reconsider the critical path. By combining new critical path thinking with smartphones to streamline response, an organisation will improve the way operators and engineers communicate within a manufacturing environment, from initial alert through to resolution.
There is no doubt that over the next decade investments in robotics, AI and IoT will transform manufacturing processes. But whatever innovation is introduced to the production line - and the deep insight, sophistication and early warning these systems will give into potential issues - will only deliver value if companies can respond intelligently and effectively.
In the Industry 4.0 world of the future, AI enabled machines may well be self-learning and able to auto-correct. In the meantime, it is those companies able to use a smart approach to communication, based on a fine-tuned critical path, that will be able to achieve the incremental efficiency gains demanded by a government keen to see the UK rise up the productivity ranks.
Fluent.ai x BSH: Voice Automating the Assembly Line
Fluent.ai has deployed its voice recognition solutions in one of BSH’s German factories. BSH leads the market in producing connected appliances—its brands include Bosch, Siemens, Gaggenau, NEFF, and Thermador, and with this new partnership, the company intends to cut transition time in its assembly lines.
According to BSH, voice automation will yield 75-100% efficiency gains—but it’s the collaboration between the two companies that stands out. ‘After considering 11 companies for this partnership, we chose Fluent.ai because of their key competitive differentiators’, explained Ion Hauer, Venture Partner at BSH Startup Kitchen.
What Sets Fluent.ai Apart?
After seven years of research, the company developed a wide range of artificial intelligence (AI) software products to help original equipment manufacturers (OEM) expand their services. Three key aspects stood out to BSH, which operates across the world and in unique factory environments.
- Robust noise controls. The system can operate even in loud conditions.
- Low latency. The AI understands commands quickly and accurately.
- Multilingual support. BSH can expand the automation to any of its 50+ country operations.
How Voice Automation Works
Instead of pressing buttons, BSH factory workers will now be able to speak into a headset fitted with Fluent.ai’s voice recognition technology. After uttering a WakeWord, workers can use a command to start assembly line movement. As the technology is hands-free, workers benefit from less physical strain, which will both reduce employee fatigue and boost line production.
‘Implementing Fluent’s technology has already improved efficiencies within our factory, with initial implementation of the solution cutting down the transition time from four seconds to one and a half”, said Markus Maier, Project Lead at the BSH factory. ‘In the long run, the production time savings will be invaluable’.
Future Global Adoption
In the coming years, BSH and Fluent.ai will continue to push for artificial intelligence on factory lines, pursuing efficiency, ergonomics, and a healthy work environment. ‘We started with Fluent.ai on one factory assembly line, moved to three, and [are now] considering rolling the technology out worldwide’, said Maier.
Said Probal Lala, Fluent.ai’s CEO: ‘We are thrilled to be working with BSH, a company at the forefront of innovation. Seeing your solution out in the real world is incredibly rewarding, and we look forward to continuing and growing our collaboration’.