With the widespread availability of democratized data, manufacturers are experiencing a surge in efficiency and productivity.
In a 2023 report, McKinsey dropped a bombshell. Industrial manufacturing is at a tipping point, with the market changing and competition coming from unexpected places. According to the firm, software is emerging as a driving force, making intelligent operations no longer a luxury but a necessity.
Manufacturers are shifting focus from simply producing goods to optimizing every aspect of their operations. The goal? Reduce costs, increase revenues, and enhance overall profitability. Let’s look at what intelligent manufacturing operations have in store and how leveraging the right software with democratized data can drive significant economic gains.
Reducing Costs through Intelligent Operations
Companies can’t rely on traditional cost-cutting strategies because manufacturing is too complex. The next wave of cost reduction leverages advanced software for predictive maintenance, energy efficiency, and inventory optimization.
Predictive Maintenance:
Originally, maintenance followed a reactive or scheduled approach. Equipment was either fixed after a failure or serviced at regular intervals, often leading to unnecessary repairs or unexpected downtimes. Predictive maintenance, however, uses machine learning to analyze data from sensors and machinery to anticipate equipment failures. Manufacturers can schedule maintenance during non-peak times, reducing unplanned downtime and optimizing maintenance schedules.
Financial Impact: Imagine a car manufacturing plant implementing predictive maintenance across its assembly line. Previously, unexpected failures of robotic arms caused significant production halts. Using predictive maintenance, the plant can predict when a robotic arm will likely fail, schedule repairs during planned downtime, and avoid unplanned stoppages. This approach reduces maintenance costs, minimizes production losses, and extends the lifespan of the robotic arms. As a result, the plant achieves smoother operations and significant cost savings, directly enhancing its profitability.
Energy Efficiency:
In the past, energy consumption in manufacturing was managed using basic control systems, often leading to significant energy waste. Intelligent energy management systems now employ sophisticated algorithms to monitor and optimize energy consumption, predicting usage patterns and adjusting energy use based on production demands and external factors like weather conditions.
Financial Impact: Suppose a pharmaceutical company integrates intelligent energy management systems in its production facility. By analyzing energy usage patterns, the company identifies that HVAC systems are running at full capacity, even during non-operational hours. The company reduces its energy consumption by optimizing the HVAC usage based on actual production schedules and weather conditions. This leads to lower energy bills, reduced operational expenses, and supports the company’s sustainability goals. Improved energy efficiency also enhances the company’s reputation as an environmentally responsible organization, attracting customers and partners who value sustainability.
Inventory Optimization:
Traditional inventory management relied on periodic reviews and manual adjustments, often resulting in either overstock or stockouts. Advanced analytics and real-time data now empower manufacturers to maintain optimal inventory levels, accurately forecasting demand and monitoring inventory in real time.
Financial Impact: Think of a consumer electronics manufacturer employing advanced inventory optimization techniques. Previously, the company often faced excess inventory of specific components, tying up capital and incurring high holding costs, while other components frequently ran out of stock, causing production delays. With real-time data and predictive analytics, the company can now accurately forecast demand and maintain optimal inventory levels. This reduces excess stock, lowers holding costs, improves cash flow, and ensures that production runs smoothly without interruptions. Meeting customer demands promptly enhances sales and customer loyalty, ultimately boosting the company’s profitability.
See also: Key Use Cases for Industrial Connectivity in Manufacturing
Increasing Revenues through Intelligent Manufacturing
While reducing costs is crucial for business stability, businesses don’t want to stop there. Increasing revenue is also part of integrating cutting-edge software into the manufacturing chain.
Enhanced Product Quality:
Traditional manufacturing relied heavily on post-production inspections to identify defects, often resulting in significant waste and rework. Intelligent manufacturing systems, however, harness advanced data analytics and machine learning to monitor and control production processes in real time. This shift from reactive to proactive quality control allows for immediate adjustments based on predictive analytics, ensuring consistent product quality and optimizing the entire production line.
Financial Impact: Imagine an industrial equipment manufacturer utilizing intelligent systems to maintain high product standards. Previously, defect rates led to more frequent returns and dissatisfied customers. Now, by continuously monitoring production quality, the company reduces defects and returns, boosting customer satisfaction. This leads to higher sales and repeat business, ultimately increasing revenue.
Faster Time-to-Market:
In the past, product development in manufacturing involved lengthy cycles of physical prototyping and testing, causing delays in market entry. Today, leveraging digital twins and advanced simulation tools allows manufacturers to create virtual models of products and processes. These digital twins enable comprehensive testing and optimization in a virtual environment, drastically reducing the need for physical prototypes and shortening development cycles.
Financial Impact: Consider an oil and gas equipment manufacturer using digital twins to prototype and test new drilling equipment virtually. Traditionally, development cycles were lengthy, delaying market entry. Now, (just like oil and gas companies using digital twins to simulate asset management and forecast potential new sites) the company is able to speed up development. This agility allows them to capture market opportunities swiftly and increase revenue through timely product launches.
Customization and Flexibility:
Historically, customization in manufacturing was limited and costly, often resulting in extended lead times and higher expenses. Intelligent manufacturing now enables mass customization by integrating flexible production systems with customer-specific data inputs. Advanced manufacturing technologies, such as additive manufacturing and modular assembly lines, allow for the efficient production of customized products. Data from customer orders, preferences, and market trends is fed into the manufacturing process, enabling real-time adjustments and personalized production without significant cost increases.
Financial Impact: Picture an industrial parts manufacturer adopting intelligent manufacturing for mass customization. Previously, customization was cost-prohibitive and strictly limited to a few scenarios. Now, they can efficiently produce customized parts catering to specific industrial requirements. This opens new revenue streams and expands their market share, driving higher sales through tailored products.
Democratized Data is Key
So why now? Manufacturing is recovering from pandemic-era disruption and grappling with new customer demands, making it all the more willing to adopt technology. But the critical missing piece is democratized data.
With the widespread availability of democratized data, manufacturers are now experiencing a surge in efficiency and productivity. This transformation is driven by the seamless integration of advanced software solutions that are able to leverage that real-time data. As a result, companies are chasing unprecedented agility and performance, ensuring long-term profitability and competitive advantage in the market. Democratized data has become the catalyst for unlocking the full potential of these technologies, leading to sustainable growth and success in the manufacturing industry.
