Sustainability in Manufacturing
Published on : Wednesday 08-03-2023
Industry 4.0 offers a significant opportunity for manufacturers to drive sustainability and reduce their environmental impact, says Bala Chitoor.
The Manufacturing industry has always been a major contributor to global economic growth and in the process creating job opportunities, but it has also been a major source of environmental pollution and carbon emissions. As the world becomes increasingly conscious of the need to address the issue of climate change and the need to promote sustainable development, the manufacturing industry is under pressure to reduce its environmental impact. Fortunately, the emergence of Industry 4.0 technologies has opened up new opportunities for manufacturers to optimise their operations and drive sustainability. We will explore how Industry 4.0 is driving sustainability in manufacturing, what benefits it offers, and how companies can implement it effectively.
Industry 4.0 & Sustainability – Utilities, Waste, Staff Safety & Security
Carbon footprint results in several environmental problems including air pollution, climate change, water pollution, thermal pollution, and solid waste disposal. India’s manufacturing sector alone generates 68% of our national carbon footprint as per Forbes, a figure 20% higher than the global average. Thus, sustainability will soon become a critical factor in the segment’s digital transformation journey.
Industry 4.0 addresses digital transformation of factories using an integrated approach of automation, AI, and hybrid cloud to address operational efficiency and sustainability. Today’s smart plants are driven with automation, where machines, IIoT devices, Machine Learning and AI help reduce energy, water, waste and emissions. Anomalies are detected to spot variations in patterns and early alerts with suitable automatic actions can result in reduction of wastage.
I am proposing a set of interrelated actions that can help drive an organisation’s sustainability initiatives and set in motion Digital Transformation that is comprehensive and impactful at the same time.
Smart utilities
Energy, Water, Air and Gas that support factory operations must be monitored, measured, and controlled. Meters can be connected wired or wirelessly (retrofits) to collect data regarding usage, quality, flow, pressure, temperature, etc. Key Performance Indicators (KPI’s) with proper threshold and alarms can ensure that such utilities are performing efficiently.The data with context of date and time can be trended to understand patterns and ML/AI can detect anomalies in any of these utilities. Immediate attention to such events can help reduce wastage and help streamline consumption.
Optimise plant infrastructure
Factories supporting infrastructures such as Industrial Chillers, Compressors/Pumps/Fans, etc., consume a lot of power. Their performance is thus critical to ensure uptime and reduce energy. These systems must be continuously monitored with suitable KPIs to ensure peak performance. Operational KPIs must be enabled on such automation tools with thresholds defined for each specific system based on their defined operational values.
High performing machines
High performing machines need to be monitored for run time, idle energy, and specific energy. Run times determine the calendar for preventive maintenance that ensures peak performance and lower energy. Energy drain during idle time must be monitored and controlled based on the production load. Specific energy during production could be monitored, trended, and benchmarked against itself and against similar machines from the same manufacturer. Any anomalies detected must be attended to immediately to ensure energy is optimised.
Worker health, safety & security
A healthy, safe and secure work environment is now critical to drive social sustainability, a key determinant in company sustainability. Social sustainability determines the relationship between the employees and the organisation on a long-term basis. Automation can baseline the norms for building health, employee safety as well as security. Occupational Health and Safety measures aligned to HSE (Health Safety Environment) systems and processes must be enabled with sensors and benchmarked against respective industry standards of safety. Other automation measures like tracking lone worker and un-intended workers, fall detection, SoS alarms, etc., can be implemented with indoor location tags. These help in improving worker safety and ensure faster emergency evacuation. Surveys have also shown that retention of employees is higher with organisations deploying a sustainability program.
Optimum power factor
Unmanaged power factor leads to power losses and additional penalties. The savings can be anywhere from 1% to 30%. Automatic power factor compensation helps in correcting the excess reactive power generated by inductive loads in industries. While Automatic Power Factor Correction (APFC) panels are available, they need to be connected to a common platform that measures the power factor from the meters. With an efficient use of this device, we can reduce the apparent power demand charges.
Load management in machines
Machine operations with improper load management can lead to loss of idle power as machines are being run in batches to address lower loads. With proper sensor enabled machines and connectivity, collecting real-time data has become critical for load adjustment, with real-time usage alerts and usage pattern insights these systems help prepare a concrete load optimisation plan. Proper load scheduling can help such idle time reduction and wastage of idle power.
Diagnose & detect faults
Establish advanced fault detection and diagnosis framework across infrastructure, machines, and utilities. This can be implemented using a policy framework in a good open platform that allows policy definitions. Policies that connect multiple sources of data across systems, devices and machines and correlate these data to understand possible faults must be created. These policies can be fine-tuned over time and can become internal best practices and IP of your organisation. Correcting these faults early will lead to reduced utility wastage and hence support sustainability.
Preventive & predictive maintenance
Issues like fouling, bearing faults, metering outliers, run hours and process bottlenecks can be detected while they are occurring with Condition Monitoring and anomaly detection. Power is the best source of detecting such developing conditions and the addition of thermal or vibration sensors with suitable algorithms and domain skills in hydraulics, thermodynamics, etc., will help predict likely faults in advance.
Refined supply chain
Process delays can be tracked by tracking idle status of machines in a production line and hence a formulated action to address such delays must be implemented. This can reduce losses related to energy, water, air, and gas that are driving such production machines.
Reduced raw material consumption
In process industries, the use of raw materials like polymers, etc., can be controlled using sensors and a closed loop system that measures the outcomes. Machine Learning and AI can determine the actual amount of raw material that is needed for a specific outcome and hence reduce wastage of raw material as well as damaged or wasted production.
Zero waste & emission
Measuring of hazardous and non-hazardous wastes as well as emission in industries must be automated with weighing scales and appropriate sensors. A waste reduction, recovery and recycle process can be established to help achieve minimal or Zero Waste and Emission.
An outcome led platform approach
The foundation of implementing any digital transformation solution is to engage an organisation that has technical and domain skills, and more importantly, own the outcome of such a transformation. The need is to define and deploy a platform that is not just supporting the current need, but is scalable to address other I4.0/I5.0 needs. The platform itself must be secure, scalable, and agile. The platform must connect to a range of devices across protocols to collect and aggregate data, must support custom thresholds, ideally have a policy engine, must support an ML/AI engine for anomaly detection and predictive maintenance, also provide a method to also collected residual data that is not collectible from the machines directly. The platform must support analysis, benchmarking, comparisons, baselining and report on sustainability and ESG.
Conclusion
In conclusion, Industry 4.0 offers a significant opportunity for manufacturers to drive sustainability and reduce their environmental impact. By optimising energy consumption, reducing waste, enhancing supply chain sustainability, and increasing productivity, manufacturers can help create more sustainable, efficient, and profitable businesses. To implement Industry 4.0 effectively, manufacturers must identify their key sustainability challenges, develop a clear strategy and roadmap, and be prepared to invest in new technologies and most importantly build the required skills for people who can work with these technologies. By doing so, they can help build a more sustainable future for the manufacturing industry and the planet as a whole.
Bala Chitoor is the Founder & CEO of Flamenco Tech, a Connected Factory Solutions Partner. He is the Technology and Platform specialist for Digital Blanket; an IoT & AI enabled Connected Business Platform for Factories & Commercial Real Estate. Bala is also the Co-Founder of Future IP Group and its group companies, JaMocha Tech & Vacus Tech.
Bala set up Network Solutions’ (Netsol) international operations. Netsol was later fully acquired by Intel. At Intel, Bala Chitoor was the Business Head for Intel Solutions Services (India, Australia, Malaysia and Singapore).
