The growing list of challenges placing strain on supply chains in the 21st century seems nearly endless: Globalization has introduced unprecedented complexity with raw materials and component parts alike being sourced from every corner of the earth; uncertainty has been introduced as the result of trade tensions and other political shake-ups; and with margins tightening, companies are being pushed to engage in less make-to-stock and more just-in-time manufacturing. Moreover, unexpected crises can wreak havoc on the ability for supply chains to function properly as well. Even before the COVID-19 pandemic, catastrophes such as the 2015 Tianjin port explosion, which shut down transportation to more than 160 ports in 180 countries, have demonstrated the potential perils of global supply chains.
In addition, as mass customization and rapid order fulfillment move from luxury to expectation, customers themselves are calling more of the shots, creating demand-side pressure. Businesses looking to stay afloat have a tall order in front of them if they are to remain in operation.
Luckily, advances in technology such as cloud computing, big data analytics, and simulations are helping to clear the hurdle. By creating real-time visibility and fostering scalable collaboration, the cloud allows stakeholders across an entire supply chain to remain on the same page. Likewise, powerful software simulations fed by large swathes of data can allow companies to design and optimize models for transportation, warehousing, and distribution in a no-risk environment, yielding previously unimaginable gains in efficiency.
Bookending from these trends, the Industrial Internet Consortium recently launched the Supply Network Dynamic Simulation Test Drive, a partnership platform developed by Singapore’s Advanced Remanufacturing and Technology Centre to help manufacturers optimize the design of their supplier networks to minimize bottlenecks in supply and demand. The Industrial Internet Consortium also offers several other “Test Drive” partnership opportunities, which are short-term, rapid-engagement pilot projects that allow end-users to employ and adopt Industrial Internet of Things (IIoT) technologies by developing three- to six-month use cases based on specific problems.
The Supply Network Dynamic Simulation Test Drive will enable end-users to develop virtual optimization models to evaluate risks and countermeasures before deployment in the real world. For example, distribution centers that best serve customers can be identified by calculating the cost savings they will allow for in transportation and warehousing prior to real-world logistics reconfigurations. Similarly, manufacturers can experiment with various “what-if” scenarios to assess the effects of changing inventory or sourcing policies in a supply chain.
Other potential applications include: Evaluation of product and customer segmentation strategies for differentiated supply chain design and operating policy; optimization of supply chain networks through data-backed insights into the real behavior of the supply chain; and improvement of supply chain performance by altering network structure and product flow.