Industry 4.0: Optimization Opportunities around Eight Value Drivers
This is the sixth in a multi-part blog series that focuses on Industry 4.0 in the manufacturing industry.
In order to identify and prioritize opportunities along the digital thread, McKinsey has identified the eight value drivers that significantly impact a typical manufacturing company’s performance. They found that for each of these value drivers, Industry 4.0 levers exist that typically lead to improvements that companies can leverage to systematically identify Industry 4.0 potentials.
Manufacturing companies seeking to realize their full capabilities around 4.0 should consider the following:
- Resource/process – Improving a process in terms of material consumption, speed or yield drives value.
Example: Industry 4.0 levers to improve process/resource effectiveness in real time yield optimization, as employed by a cement kiln at ABB. “At this kiln, a computer-based system for controlling, stabilizing and optimizing process variables was introduced. It mimics the actions of an ‘ideal’ cement plant operator focused on achieving particular targets,” reports McKinsey. “Based on the actual measures, adjustments to the process necessary to achieve the ideal process are calculated by the system. The newly calculated values for kiln feed, fuel flow and fan damper position are then sent automatically to the kiln control system to drive the process towards the optimized kiln targets. Typically, real-time process optimization yields an improvement in throughput of up to 5 percent.”
- Asset utilization – Improving asset utilization drives value by making the best use of a company’s machinery lot. This is particularly true in asset-heavy industries with expensive machinery. A loss in expenditures and revenue happens every time a machine is down.
Example: “Industry 4.0 levers like predictive maintenance can thus drive value by decreasing planned machine downtime, unplanned machine downtime or changeover times. For example, GE10 offers predictive maintenance in which remote sensors collect and report data on the condition of the machinery,” says McKinsey. “Based on the sensor data, early signs of problems are detected for timely correction at minimal costs, maintenance resources can be prioritized and optimized and machine availability can be increased. Typically, predictive maintenance decreases the total machine downtime by 30 to 50 percent and increases machine life by 20 to 40 percent.”
- Improving labor productivity can drive significant value – “This value can be captured via levers that reduce waiting time (e.g., completion of previous process step in manufacturing, delayed delivery of a good in manufacturing or a prototype in R&D) or increase the speed of workers’ operations by reducing the strain or complexity of their tasks,” says McKinsey.
Example: Etalex, a Canadian manufacturer of warehouse furniture, introduced collaborative robots to increase labor productivity in its plant. The company had two problems: “Workers were manually loading press brakes with large metal parts, which is a physically straining task. Furthermore, the limited space did not lend itself to the addition of large machinery. Etalex therefore introduced human-robot collaboration, allowing humans and machines (collaborative robots from Universal Robots) to work in close proximity to each other without risking injury of the workers,” reports McKinsey. “Due to a built-in force control, the robot automatically reacts in case of contact with humans and slows down or even pauses its movements. Etalex was able to increase throughput, such that sales were increased by 40 percent, while maintaining the same employee base.”
- Having excess inventory ties up capital, causing high capital costs – So, of course, reducing that surplus can lower costs. Industry 4.0 levers target those various drivers of excess inventory.
Example: Würth’s iBins uses intelligent camera technologies to capture the actual fill level of a supply box. “The box is wirelessly connected and automatically reorders supply based on accurate fill information. Through levers like this real-time supply chain optimization, Industry 4.0 can typically reduce costs for inventory holding by 20 to 50 percent,” says McKinsey.
- Quality – Improving quality is a value driver. Products requiring rework lead to extra costs (for machine time, material and labor). “These quality inefficiencies are caused by unstable processes in manufacturing, deficient packaging in the supply chain or distribution and unskilled installation,” reports McKinsey. “Eliminating issues during the value creation process using Industry 4.0 levers such as SPC, advanced process control (APC) and digital performance management can create value.”
Example: Toyota uses advanced analysis for real-time problem solving during the production process. “Real-time data analytics and APC enable real-time error corrections to minimize rework and scrap. We typically see a decrease in costs related to suboptimal quality of 10 to 20 percent through Industry 4.0 quality levers.”
- Supply/demand match – According to McKinsey, only a perfect understanding of customer demand—about the quantity and the product features customers are willing to pay for—maximizes the value captured from the market. So optimizing the match of supply to the actual demand via Industry 4.0 levers can seize value potential.
Example: “One automotive OEM uses the data-driven design lever by gathering information via the online configurator on its website and actual purchasing data to identify the product options that customers are willing to pay a premium for,” reports McKinsey. “As a result, the product offering could be limited to only 13,000 relevant options, thereby significantly decreasing development time and production costs.”
- Time to market – Bringing a new product to market earlier creates additional value by increasing revenue and leveraging early-mover advantages. So those Industry 4.0 levers that speed up the development process help drive this value.
Example: McKinsey points to an extreme example, Local Motors. “This manufacturer produces cars almost completely through 3D printing, with a design crowd sourced from an online community. They were able to reduce the development cycle from the industry average of six to seven years to one year and achieved a massive cost reduction in R&D. Other OEMs, e.g., Vauxhall and GM, also use 3D printing and rapid prototyping. Typically, Industry 4.0 levers can reduce the time to market by 30 to 50 percent.”
- Service/aftersales – Because operation costs are driven by service costs—maintenance, repair—and unexpected machine downtimes, offering solutions to decrease these for the customer opens up additional value potential.
Example: One of these service levers is remote maintenance, and Secomea provides an example of its success. “The company offers software solutions that allow technicians to establish a secure remote connection to industrial equipment to carry out a diagnosis without visiting the site,” says McKinsey. “A customer reported that 50 percent of the issues that normally require an on-site visit could be resolved remotely. Typically, we see maintenance cost reductions of 10 to 40 percent through remote and predictive maintenance.”
Want more 4.0? You can LEARN ALL ABOUT the Industry 4.0 revolution and how MarkLogic is helping customers industrialize their data!
Also, check out previous blogs in this series: