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Sustainable Manufacturing Digital Continuity Strategy
Sustainable manufacturing digital continuity (SMDC) is the integration of digital technologies into the manufacturing process to improve sustainability and reduce waste which translate into environmental, social, and economic sustainability throughout the manufacturing lifecycle. Manufacturers can leverage SMDC strategies to optimise their operations, reduce their environmental footprint, and enhance their competitive advantage by leveraging digital technologies such as the Internet of Things (IoT), big data analytics, artificial intelligence (AI), and digital twin models.
This approach promotes a circular economy model where products are designed for reuse and recycling, and manufacturing processes are optimised for energy and resource efficiency. SMDC also facilitates transparency and collaboration across the supply chain, enabling manufacturers to track and share sustainability metrics with stakeholders, including customers, investors, and regulators.
Here are the top 5 SMDC strategies for manufacturers:
1. Adopt a circular economy approach
Manufacturers can adopt a circular economy approach by designing products for reuse, refurbishment, or recycling. This approach involves the use of sustainable materials and processes, as well as the recovery and recycling of valuable resources. Digital technologies such as predictive maintenance and real-time monitoring can optimise the performance of products and prolong their lifespan, reducing waste and improving sustainability. A powerful engineering data analytic tool like Cornerstone from camLine (Elisa IndustrIQ company) can assist in the Design of Experiment (DoE) process, to reduce overall experimentation effort to essentials. Cornerstone explorative data analysis enable certain design and perform process simulation in digital way rather than physical experiment which eventually ends up in waste.
2. Implement a digital supply chain
Manufacturers can implement a digital supply chain by leveraging digital technologies such as suppliers’ quality management, customers’ quality management, and RFID to track products quality and throughout the entire supply chain. This enables end-to-end product traceability and enhances transparency and accountability. It supports manufacturer working more closely with their subcontractors and suppliers and customers at globally distributed production sites by implement and improve mandatory quality standards in the entire supply chain to ensure that the products are sourced sustainably and ethically. Digital supply chain technologies can also optimise logistics and transportation, reducing waste and improving sustainability.
Digital solutions can also help to reduce the number of incoming quality inspection or setup QC Lab. LineWorks SQM/CQM from camLine has assisted many of their customers to avoid resource wastage in incoming inspection. A recent scenario gaining importance is supply chain disruption due to geopolitical impacts. In this case, digital solutions such as Supply Quality Management should be able to advise on possible alternative sources of supply or to develop a second source of supply for the manufacturer. In such a solution, the manufacturer should also be able to define its list of approved suppliers to respond to sudden changes in the geopolitical situation.
3. Deploy a manufacturing execution system (MES)
A manufacturing execution system (MES) is a digital system that manages and monitors the production process in real-time. MES existence in the market for decades, it evolves from simple production scheduling and tracking to more extended functionalities such as quality control, maintenance management, recipe management and towards as a digital twin supported with AI processing for a running factory. MES helps to optimise production by automating processes, reducing waste, and improving quality control. By deploying an MES, high-tech manufacturers can improve sustainability and reduce their environmental footprint, while also enhancing their operational efficiency and competitiveness. Out-of-the-box single source MES or a modulars based MES are available on the market. Finding the right MES partner with a flexible and scalable platform is one of the key success factors. camLine, with its more than 30 years of implementation experience and the LineWorks Suite, has mastered many successful implementations together with its customers.
4. Utilise data analytics
Manufacturers can utilise data analytics to optimise their operations and improve sustainability. Data analytics can provide insights into energy consumption, production efficiency, equipment efficiency and waste reduction, enabling manufacturers to identify opportunities for continuous improvement. By leveraging data analytics, high-tech manufacturers can reduce their environmental impact while also enhancing their operational performance. It is not necessary to redefined data analytics for every use cases. There are plenty of good know-how from the industries has been developed available through digital technology. Best practices can be shared from digital solution provider or subject matter expert in the respective industry.
5. Explore AI use cases
Artificial intelligence (AI) can be used to optimise manufacturing processes and improve sustainability. AI can be used to optimise production scheduling, reduce energy consumption, root cause analysis, and improve quality control. Here are some examples:
- Process optimisation: Engineers can collaborate with AI to optimise manufacturing processes by analysing data from sensors and production equipment. AI can identify patterns and anomalies in the data, enabling engineers to identify opportunities for improvement. For example, AI can detect changes in equipment performance that may indicate a need for maintenance or repair, allowing engineers to act before a failure occurs.
- Quality control: AI can be used to improve product quality by analysing data from sensors and cameras or AOI (Automated Optical Inspection) equipment to detect defects or deviations from specifications. Engineers can collaborate with AI to develop algorithms that can identify and classify defects with high accuracy, enabling them to take corrective action in real-time.
- Predictive maintenance: Engineers can collaborate with AI to implement predictive maintenance strategies that can improve equipment uptime and reduce downtime. By analysing data, equipment logs from sensors and production equipment, AI can predict when maintenance is required, enabling engineers to schedule maintenance proactively and avoid unplanned downtime.
- Material selection and optimisation: Engineers can collaborate with AI to optimise the selection and use of materials in the manufacturing process. AI can analyse data on material properties, performance, and cost, enabling engineers to make informed decisions on material selection and usage. This can lead to improved product performance, reduced waste, lower manufacturing costs and help develop single source risk mitigation plan via AI.
Sustainable Manufacturing Digital Continuity (SMDC) can provide significant benefits to manufacturers by increasing their sustainability and operational efficiency and improving their competitive advantage. By applying the 5 strategies above, manufacturers can optimise their operations and achieve their respective sustainability goals.
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