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Background
Thoroughly assessing the vulnerabilities present in the supply chain allows for the development of robust strategies to enhance resilience, thereby guaranteeing the availability and sustainability of critical materials and components essential for long duration energy storage [LDES] technologies.
By gaining a comprehensive understanding of these vulnerabilities and taking proactive measures to address them, we can effectively mitigate potential disruptions and ensure the long-term viability and efficacy of clean energy technologies. Additionally, having a quantitative benchmarking framework that evaluates both the resilience and sustainability of the supply chain, can provide valuable insights for comparison against the established lithium-ion technology.
Challenge
One of the major challenges with supply chain optimisation is the fact that post-decision, diverse forms of fresh information emerge [such as customer demands, machinery breakdowns, or the performance of novel materials] etc. This sequential progression necessitates making decisions prior to the influx of new information, compelling us to navigate the terrain of optimization under uncertainty, seeking optimal decisions amid evolving circumstances.
Next-gen SCM Models
Next-gen supply chain management models for LDES liftoff, can be designed to handle diverse scenarios with utmost efficiency. The models should be capable of handling a variety of scenarios from finite horizon, settings involving a single decision [decision, information, stop], dual decisions [decision, information, decision, stop], a random number [stopping when a condition is met], or even an infinite number of possibilities.
The model should also have the capabilities to tackle a range of new SCM challenges that begin with fresh information preceding the initial decision, commonly known as a "context." With the integration of natural language processing, users should be able to seamlessly chat with the model and unlock valuable insights within their supply chains. Our SCM optimisation model ChainSynQ™ seeks to do just that.
Conclusion
In summary, Peniel Impact envisions a supply chain management and logistics ecosystem that draws significant inspiration from industry pacesetters like Amazon. Our vision entails a seamless integration of all the essential components that constitute LDES technologies, ensuring their availability on-demand and mirroring the efficiency demonstrated by leaders in the field such as Amazon.