In the current environment, disruptions within the manufacturing industry are a major concern. With COVID-19 changing so many aspects of our daily lives, having access to both essential and non-essential goods is critical to ensuring people have what they need to get through, and to keeping our economy as stable as possible throughout these uncertain times.
Manufacturers are a crucial part of the supply chain and now, maybe more than ever, they are at the mercy of the quickly changing whims of supply and demand. Consider the heightened demand for items such as toilet paper and baking flour. In both cases, manufacturers need to find ways to be more efficient, and increase production. On the other hand, decreased demand in certain items at this time may mean that manufacturers that are capable of diversifying are better positioned to function in such a volatile market. Either way, getting the most out of what you already have by optimizing your asset management is key.
For more about mitigating vulnerability and disruption within the supply chain, check out our previous article Adapting to Change | “What If?” Simulators for Supply Chain Operations. However, here, we are going to look at the ways in which manufacturers in particular can leverage data, machine learning and AI to optimize asset management, and find efficiencies that will help you adapt to the new normal today, and in a post-pandemic world.
What is Asset Optimization?
Asset Optimization is a strategy to improve the effectiveness of your overall methods for asset management. This is done by increasing efficiency or functionality of items already owned, to increase your overall profitability. This might include, for example:
- Optimizing schedules, so that you do the right work at the right time
- Implementing predictive maintenance to reduce downtime and improve performance
- Using data analytics and AI to make better predictions and decisions
In the short term, asset optimization will allow you to mitigate the potential risk COVID-19 may pose to your operations. In the long-term, such a strategy will help you:
- Cut operational costs
- Improve market position
- Remain compliant with industry regulations
- Improve quality of work
- Mitigate risks and vulnerabilities
- Adapt to evolving circumstances
Given the unprecedented challenges we’re facing these days, now is the time to do more with less. If we have learned one thing from the current situation, it’s that people are adaptable — it’s critical that our businesses adapt too. Being able to pivot quickly and efficiently will be the difference between staying afloat and falling behind.
Leveraging Data and AI to Optimize Your Assets
Data and AI solutions can help optimize your assets and keep operations moving smoothly. Ingest, transform and engage with your existing data to find valuable insights, test outcomes, and make accurate predictions.
- Gain meaningful insights to help find efficiencies
- Predict likely problems before they occur, based on historical and real-time data
- Extend asset lifecycles by reducing downtime and improving productivity
- Build “What If?” simulators to challenge your assumptions and help you pivot
With the right knowledge, you can create better processes for everything from maintenance schedules, to how and when you operate any given machine. Implementing AI will allow you to take this a step further, knowing that relevant data is always being analyzed in real-time, so that results are always up to date.
Use Case | Asset Optimization Model
Lixar was approached by a company that had built a data model to optimize the output of their various system assets. However, the existing model was not only slow, but was not even operating correctly. We were asked to build a new model that could meet the following two criteria: 1) the new model must outperform the existing model in terms of optimizing asset usage; and 2) the new model must be able to generate schedules and be re-run as necessary, to accomodate last-minute constraints. Moreover, due to the complex nature of the manufacturing process, the model had to be flexible enough to operate efficiently on multiple systems in unique environments.
Lixar successfully created a functioning data model with new data inputs, including several variables and constraints. This initial asset optimization model meets both criteria, outputting CSV files and graphs to generate optimized schedules. So far, the model has generated a significant revenue increase. The model is now being deployed on our modern data platform, HeroPath, upon which we will provide models for each distinct environment, orchestrated to execute on a regular basis. As an end-to-end scalable solution, HeroPath also offers the potential to leverage machine learning and AI in the future to automate models, for further time and cost savings.
Where to Begin | HeroPath
If you are ready to do more with less, and are looking to get started on optimizing your assets, you may want to begin with a modern data platform. Our HeroPath solution is designed to be flexible and scalable, so that it can be delivered quickly and within your budget. By leveraging Azure Cloud and other best-in-class components such as Databricks and Data Lake, our data experts can stand up your new pipeline in just weeks. Once HeroPath is up and running, you have access to real-time analytics, meaningful insights, and of course, you’ll have the foundation you need to begin optimizing your assets.
The future is uncertain, but we do know that times are changing and we all have to adapt to a new normal. The quicker we can do so, the better. Getting the most out of our existing assets is the most efficient and cost-effective way to stay relevant, keep up with the changing landscape, and be prepared for the short and long-term economic impacts of the current pandemic.
For more information about our data and AI services, including HeroPath, please contact us at email@example.com.