Within industrials, shocks to both supply and demand have significantly decreased production volumes or stopped operations. For instance, all major automotive OEMs in Europe have shut down their production networks, resulting in the breakdown of entire value chains. Where the business has continued, physical-distancing measures are dramatically altering operations, employee responsibilities, and staffing.
To navigate the current crisis and reach the next normal that will emerge after the pandemic abates, companies must embark on a journey with three horizons, each of which involves different questions:
Industrial IoT (IIoT), a major element of Industry 4.0, can help companies as they proceed on this journey. It has demonstrated its value on many occasions over the past few years, but some skeptics still doubt its worth and elected not to make bold investments in this area. What’s more, few business leaders view IIoT as a critical improvement lever in times of crisis, especially if their organizations have not previously explored it.
Reimagine and reform: Leveraging IIoT to emerge stronger post-crisis
The pandemic will have a lasting effect on businesses, even after it abates. On the customer side, industrials might see a permanent shift toward contactless delivery or greater end-user configuration. They may also decide to implement new strategies along the entire supply chain to avoid disruptions similar to those they encountered in early 2020.
Supply-chain integration across the value chain
IIoT facilitates real-time data exchange between all supply-chain participants, creating an integrated view of production programs, scheduling, inventories, quality, and anticipated delivery times. In addition to building transparency and trust, such tools can also reduce supply-chain costs and risks—for instance, by receiving signals from connected machines when they are running out of raw materials, or by tracking the flow of materials along the supply chain using geolocation tags. With these insights, companies can optimize inventory levels, production planning, and transport utilization through a more holistic approach. (The information on inventory is used to improve planning across the supply chain, including decisions about producing materials.) Companies will also learn about supply-chain problems more rapidly, allowing them to act before they escalate.
In-line process optimization
IIoT can increase the production efficiency of single machines or entire production lines by using advanced analytics to optimize process parameters. The algorithm analyzes information on all available variables, including production, scheduling, asset condition, and input goods. Data from individual machines get combined with information about the overall production program, allowing companies to optimize machine settings based on previous and subsequent production steps. This allows companies to adjust production schedules quickly to account for changes in demand or unexpected supply-chain disruptions.