Smart manufacturing is sustainable manufacturing

Success starts with defining a manufacturing strategy. This process involves first order assessments to understand the impacts of early decisions on manufacturing requirements, including determining what to buy from suppliers, which product components make in-house, carefully selecting partners and suppliers, and where to manufacture new products. Each of these decisions will directly impact the success of a business – and choosing sustainable options is often the solution for long-term success.

Purchasing strategies can change dramatically when also considering the implications of energy use, resource consumption, carbon footprint, and circularity practices. Rather than purchasing the lowest cost components for the functional needs of a product, manufacturers need to balance costs with the associated carbon footprint of selected components. Materials and components should be sourced from a supplier who shares a sustainable mindset and the strategy for moving goods needs to be defined early on. Fortunately, digitalization and automation help reduce the burden of increased complexity in this redefined manufacturing strategy process.

By collecting and analyzing relevant data, decisions can be made with confidence. If more manufacturing capacity is required for a new product, understanding the needs and goals of a facility in the digital world can help determine new plant locations and layouts to balance the environmental impact of construction, energy use from manufacturing lines, and estimated production rates. Sustainability KPIs such as energy efficiency is simpler now that different scenarios can be evaluated in the Digital Twin.

This technology enables decision-makers to simulate everything from lighting and climate control to the environmental impact of their supply chain. Equipped with this information from the start helps organizations to make better decisions.

The next phase for integrating sustainability is in the design of lines, processes, and plants. By building a detailed model for production in the digital world first, businesses can simulate different scenarios to optimize performance across the factory environment.

When designing in the digital world, businesses can implement greater automation and streamline production to avoid lapses in efficiency. An idling machine for example, has an opportunity cost of not running, but there is an operational expense from the energy being drawn, which in turn has a carbon footprint impact based on the source of that energy, simultaneously reducing the investment costs of physical materials.

Running a motor longer than needed or transporting material further than necessary may not have a major impact on a per product basis, but these inefficiencies add up quickly. Sustainable solutions for these common problems aren’t limited to greenfield environments either. The design process applies to brownfield facilities as well. While this may seem like a monumental undertaking, it’s achieved by reorganizing manufacturing lines to fit more production capacity into the same floor space, updating processes and machinery to keep pace with market growth or, updating hardware systems to reduce energy consumption, and installing infrastructure such as solar arrays or battery storage to better capitalize on renewable energy sources.

For example, Swabian machine builder, Hugo Beck has managed to transform the packaging industry and their business with the Digital Twin. Empowered by Siemens technology, engineers used the Digital Twin to design a machine that adapts packaging to product dimensions, optimizing performance through digital simulations. Because of their innovation and commitment to finding solutions that tackle both environmental and business goals, Hugo Beck has cut energy use by 20 percent, commissioning time by 50 percent, packaging material by 30 percent, and packaging volume by 10 percent.
Overall, the Digital Twin helps businesses outline their needs earlier and evaluate many different possibilities to find sustainable processes. Poor maintenance strategies can reduce a factory’s overall performance by 5 to 20%. In other words, excess maintenance equals excess spending, making the Digital Twin a vital component for efficient factory operations.

Production planning is where investments in digitalization show value. The efficient use of materials, people, and machines, makes businesses effective. This is also where comprehensive simulations and requirement validation begins to aid decision making and the selection of supply chain partners. Moreover, organizations can create safer work conditions, better train workers, and invest in the education and up-skilling of their employees.

With data insights, businesses can select sustainable materials and optimize raw material use to minimize scrap rates. They can also simulate the impact of using recycled materials or determine which equipment providers can deliver increased energy efficiency and repairability in addition to throughput and cost. Minimizing idle times reduces energy demands and the per-unit cost of products while also contributing to a lower carbon footprint.

Understanding when a machine needs maintenance can help reduce switch-overs during production. Similarly, logistic routes can be planned to minimize transportation distances and their associated carbon emissions while also enabling flexibility with intelligent inventory management in the case of problems.

Production planning is how businesses can build connection points to enable a circular material stream. By understanding where unavoidable waste will be produced early on, plans can be made for reusing, recycling, or repurposing remaining materials.

Production execution is key to achieving sustainability goals, but tracking and enforcing sustainable processes can be a major hurdle. While simulating production during design helps find solutions, real-world complexity often requires a closed-loop connection between digital and physical systems.

Luckily, digital solutions offer opportunities to improve quality and yields. Even experienced manufacturers face inefficiencies when launching new production, leading to wasted materials, energy, and time. Integrating real-world data with a digital twin enables faster optimization, driving both profitability and sustainability.

Energy costs are rising in some regions, making efficiency more critical. Viewing execution as part of a larger system can reveal cost and emissions savings. For example, efficient motors can cut energy use by up to 30%, high-energy processes can align with solar generation, and optimizing intralogistics can reduce unnecessary factory travel, lowering both energy demand and carbon footprint.

Leading sleep products manufacturer, Pikolin, has taken their sustainability strategy seriously by incorporating Simatic Scada and Energy Management tools into their new facility. Pikolin's new factory integrates production from raw materials to finished products, ensuring high quality while maximizing efficiency. Designed for sustainability and profitability, it meets ISO 14001 and 50001 energy standards, reducing costs and enhancing productivity. As a result of their sustainable efforts, Pikolin’s facility consumes 40% less natural gas and yet has 30% more production capacity, illustrating the positive results of plant optimization.

With production in full swing, the next phase of the journey is monitoring. By continuously monitoring plants and production, manufacturers can proactively improve production. The predictive maintenance of machines to keep them operating at peak efficiency or detecting problems before they occur is part of this anticipatory strategy. How this monitoring best enhances manufacturing comes down to the KPIs of the business, but some common ones are energy consumption for machine, line, and plant level analysis, material flow and resource utilization, and worker safety,

Automation can limit non-ergonomic movements for employees to move them away from hazardous processes. But at the same time, robotics in the factory need to be safe for the workers on the floor. Not all automated tasks can be fully separate and monitoring for any unsafe working conditions will be invaluable as factories become more efficient and sustainable.

The final change on the path to sustainable production is optimization. This is where companies can attain the biggest payoff from investments. Through the continuous optimization of production, manufacturers can stay ahead of their competitors.

Integrating IT and OT data enables plant managers to identify and predict trends which allow them to proactively adjust operations and material sourcing to adapt to unplanned disruptions. This enables them to track power usage, water consumption, and supplier data, to determine the carbon footprint of production processes across the entire value chain.

In addition, when a machine or part of the manufacturing process fails, it should be looked at with an eye for repair and refurbishment. Having a digital twin of manufacturing in a closed loop with production helps make decisions like where to modify equipment to prevent failures, which parts to replace, and how to best follow repair procedures.

For example, textile technology Spinnova accelerated their fiber production by integrating automation and digital twin technology, optimizing operations and reducing time to market. Virtual commissioning streamlined factory setup, while real-time data analysis improved efficiency, identified bottlenecks, and ensured consistent quality from raw materials to finished fiber. Energy optimization further strengthened operations, making the company’s production more resilient and cost-effective. By leveraging Siemens Xcelerator technologies, Spinnova not only scaled faster but also set a new benchmark for sustainable manufacturing, proving that efficiency and environmental responsibility can go hand in hand in the textile industry.