There has been an extreme amount of ‘buzz’ around these two topics in the ready-mix concrete industry as of late. Easily misunderstood, these two topics continue to attract the attention of many and, at the same time, scare others off. To give this a fair shake, it is critical that their definitions and subsequent use cases are well understood.
Optimization, defined
Turing to ChatGPT, the definition of optimization is, “the process of making something as effective, efficient, or functional as possible. It involves finding the best possible solution to a problem by maximizing desired factors…and minimizing undesired factors.” AI is defined as, “the simulation of human intelligence in machines, enabling them to perform tasks that typically require human cognition. These tasks include learning, reasoning, problem-solving, perception, language understanding, and decision making.” There are clearly overlapping elements of the two definitions, and when we apply the use cases of each to the ready-mix concrete space, we can certainly see the natural potential.
Optimization 1.0
Optimization has been around for many years, and I had the privilege of supervising one of the largest US ready-mix concrete producers using what I now refer to as “Optimization 1.0.” 1.0 was designed to minimize user defined inputs and costs, including factors such as:
- Cost of lateness to customers, priority
- Material costs
- Travel time & Fuel burn
- Labor costs
- Customer priority
1.0 would suggest to a dispatcher what truck to assign a particular load to, what plant(s) an order should ship from, and where a truck would be rerouted to when leaving a job, all based on cost minimization. There was a lot of friction when we implemented 1.0, mainly because of the general misunderstanding that “it” was going to make all the decisions for the dispatchers, and that they would soon become obsolete. That, simply put, would not be the case.
AI potential for the ready-mix concrete industry
AI is the new kid on the block, well, kind of, and the AI potential for the ready-mix concrete industry is just beginning. We have all been using AI to some extent over the years, just not necessarily realizing it, or categorizing it as such. When did AI become AI anyway? That is a broad, gray area at best, and it is, in my opinion, that any data aggregation exercise and subsequent analysis is a general form of AI. A rapid evolution in AI in recent years is due to a colossal increase in computing power, advanced machine learning, and cloud-based solutions tied together via APIs. This has really been the catalyst that has taken AI to the level of awareness and use that we see today.
AI potential for the ready-mix concrete industry will be centered here:
- Real time driver & truck-based historical performance data
- Intelligent customer pricing tools leveraging historical customer performance data for dynamic pricing suggestions
- Automated chat ‘bots ‘ integrated with dispatch systems
- Dynamic cost calculators considering real-time variable inputs, such as weather, traffic conditions, driver performance, truck types, plant performance, material costs, and mix management
- Plant maintenance alerts and dynamic PM schedules
- Automatic plant tuning, such as Batch AI (formerly MIntelligent Feed) by Command Alkon
- Evolution of Optimization 2.0, dynamic suggestion-based dispatching, based on deep data dives, coupled with real-time inputs, while exceptions are pushed to dispatchers
- Automation of redundant, manual tasks at dispatch and plant levels
- QC tracking, feedback, and real-time monitoring and design updates
- Turbocharged data sharing, free exchange of information, via APIs across platforms
- Customer-facing applications
AI as tools
Does this mean that dispatchers and plant operators’ daily tasks will change? Perspective, patience, and careful evaluation and planning are everything. We are still relatively early in this realm, and change is inevitable. It is paramount to understand that we are dealing with tools, and when treated as such, we should expect that our daily duties and experiences can be greatly enhanced.
As Optimization and AI potential for the ready-mix concrete industry continue to evolve, I expect barriers to entry along with implementation costs to fall. Through cloud-based technology, APIs, and group think tanks, optimization and AI will become more widely accepted by the ready-mix concrete industry. It will be increasingly difficult to argue their use cases, as in reality, they inherently are designed to accomplish exactly what they are asked to do and minimize operational costs, while providing high service levels in real time.
I always recommend reaching out to industry technology leaders and ready-mix concrete companies that are leading the charge. There are surely to be some bumps along the way, but I truly believe that embracing technology can take your business to the next level and prevent others from passing you by.