Key points
Decision makers use digitalisation to reopen the work ecosystem for beyond business continuity
By 2021, $57.6 billion will be the global spending on cognitive and AI systems according to IDC. Although quality maximisation and yield optimisation are the centre of business goals, the changes in the last quarter has made remote and safe working an equally important goal.
Owing to these tremendous changes in the industry, economic growth for businesses is possible when analytical simulation of Digital Transformation (DX) becomes an essential part of this industry.
Ever since the outbreak, remote work and heightened safety at work is uncompromisable. DX is about realising its value in terms of flexibility, agility, and production optimisation under any circumstances and not just about upgrading to newer technologies but.
Sandy Shen, Senior Director Analyst, Gartner, says “This is a wake-up call” as the organisations have placed too much focus on operational needs at the expense of digital business and long-term resilience. As the operational needs are more than met, DX will be more important than ever.
Achieve safe COVID work environment with Computer Vision
In the current-COVID world with the new normal being limited employees, the success of optimum production will depend on fully automated and data-driven manufacturing systems. It is required for the operators to be on-site to supervise the processes.
But with reduced operators, social distancing, and other employee safety procedures, remote monitoring becomes the new norm. Digitalised factory seems to trend and get along well with new regulations in the manufacturing industry.
Locked down? You can still monitor, digitally.
Computer Vision, advancements in video analytics, has made remote assessment and decision making possible. Regardless of the outbreak and unavailability of the whole team on the field, the operations go uninterrupted with real-time asset monitoring for greater output quality from remote locations with video analytics.
Role-based performance dashboard allows operators, supervisors and managers access data and insights that are of interest to them on an intuitive view.
They can monitor key parameters of production – yield, run-time, quality and an end-to-end visibility of the inventories, machines, and processes via performance dashboards. Any deviations from the required set-up can be controlled from their current place.
Safety first. Achieve it with an AI-eye.
374 million non-fatal work-related injuries occur each year are the human cost to maintain global industrial economies. 98% of all accidents are preventable. Industrial leaders must act now to create safe working environments.
Post-COVID, industries will have to strictly monitor government compliances and regulations like the presence of Personal Protective Equipment (PPE) necessary for employee safety.
Additionally, they will also have to adhere to new safety measures like social distancing and people wearing masks within premises. Computer Vision alerts operators and higher ups in case of any violations of the norms.
Digitalisation creates a shield to be resilient against disruptions by facilitating flexible ways of working.
Manufacturing companies are manoeuvring with this armour to achieve the business goals amidst the pandemic. But has the current situation changed the needs of the consumer? No. Quality remains the unwavered requirement of any customer.
Quality prevails
Any manufacturers’ nemesis is wastage. It is more hurtful when even a minute deviation in quality is subjected to rework or reject. Companies are working towards optimising production to reduce off-spec and prevent capital drain.
The new regulations and the stringent quality requirements are putting more pressure on the businesses. The companies are realising that any progress – like production optimisation, yield maximisation, or operational excellence can be achieved through data-driven analytical solutions, improving competitiveness.
To solve this million-dollar quality issue, Flutura has built vertical-specific digital assistants to provide a customised solution through Operational Efficiency and Asset Uptime reliability.
Centre of Excellence with AI
One such company, a leading industrial grade adhesive manufacturer, faced the adversity of producing inconsistent product quality within the in-spec batches. The associated recall costs were too high leaving the company with an option to eliminate quality deviant batches completely.
The company relied on manual testing to identify root causes for the quality failures that was post-mortem in nature and took a greater deal of time of about 2-3 weeks. The company insisted on Golden Batches every production run to maintain brand reputation and achieve higher business value.
Previous Customer Journey
Manufacturing process industries have various metrics to measure the quality of a process such as yield rate, scrap rate, cycle time, throughput, and more. All these metrics, however, are at a process level, none tackle the challenge of assessing the quality of every manufactured batch.
Flutura recognised this and built Cerebra with vertical specific digital assistants by providing insights into batch as well as line level. Smart methods such as Quality Correlator (Scoring & Benchmarking), Quality Diagnostics and Quality Prognostics are used to assess the plants with highest economic potential to produce golden batches.
Companies have used statistics, robotics, and video technology to reduce QC costs. AI has further reduced such costs along with rework & rejects by making the QC process dynamic and self-correcting in nature. Cerebra with its quality-centric digital assistants enhances quality, efficiency, and asset uptime.
Cerebra Enabled QA Process
Look beyond the 5Ms of Manufacturing
In the nascent stages, Quality Correlator supervised machine learning algorithms and analysis prompted that quality was correlated with multiple areas like safety of the workers, change in vendor, and beyond the obvious parameters.
Quality Scoring with smart algorithms set an aggregated single score to each of the plants. Quality Benchmarking used these scores to identify and rank the plants with the highest economic turn out.
Machine learning based algorithms captured and analysed 5Ms of manufacturing. These data-driven Quality Diagnostics assisted operators to identify root causes with a single click, saving 90% of their time. The RCA used fishbone diagram in segregating the causes and generated
- “Alerts” the user of the most critical and parameter with the highest impact on the quality
- “Warns” the user of the parameters with medium impact on the quality
- “Cautions” the user of the parameters with a lower impact on the quality
Quality Prognostics helped in reducing rejects and rework mainly with its simulation that predicted the quality of the final product even before the production was completed. With what-if analysis Quality Prognostics suggested the required parametric changes to arrive at the desired quality.
Quality Prognostics ran on a closed-loop automation, i.e., the supervised learning ML algorithms alerted the operators of the impending results and suggested any changes to avoid deviance from Golden Batch quality. The operator had the authority to feed their expert opinion to the system making Cerebra learn from the situation and provide finer insights next time
Customer Journey Powered by Cerebra
Driving the future with data
Digital Transformation assists manufacturers to be nimble in the face of today’s challenges. While AI will be relied to improve productivity as well as assist employees abide by the new regulations.
Process automation, remote monitoring and on-site safe working is possible with the new automation strategies coupled with AI and will boost labour productivity by up to 40%.
Manufacturers have been investing in data collection, analytics to improve data-driven decision support. Data-driven AI can ease how operations intelligence is gathered, shared, and acted upon will be highly sought after.
