Loading and Unloading Traffic Simulation Inside an Industrial Unit
You'd be surprised at the unwanted secret negative impact that loading and unloading traffic inside your industrial unit can have on your business and its resources consumption.
Simulation allows the quantification and reduction of negative impacts of loads and unloads on your company’s image and productivity.
An industrial processing company that receives and ships materials via heavy trucks wanted to know how it can make loading and unloading more predictable and less impactful on the variety of operators. Currently, it's carried out without a set time frame. If there are workers available on the factory the operation is carried on, considering it works 24/7.
Inside the factory there is a scale by which all vehicles pass in and out. The company operates various types of materials, solids and liquids with different loading and unloading times as well as different operation requirements for the task.
In this fixed timeframe for loading and unloading, the company needs to have a waiting park for 15 trucks which is the predictable maximum number with a 95% confidence level.
In order to analyze the cargo traffic, it was first necessary to quantify this traffic. This was based on the amount of materials and raw materials traded by the company and the average load of each truck. As the various values are not fixed, it was needed to approximate statistical functions to the data, so the input of trucks would not be not uniform but varied, which brings more reality to the model.
The results collection were based on a 1 year basis, being performed several simulations of that same year to obtain data with a confidence interval of 95%.
The simulation incorporates data such as:
- Vehicle travel time between the various points of the industrial unit;
- Approximate loading and unloading times as statistical functions for each material type;
- Statistical input distributions of each type of vehicle and material within the industrial unit;
- Operator costs as well as shifts, availability and probability of their absence;
- Efficiency of loading and unloading equipment as well as their maintenance times;
With the simulation results, it's easily verified there are no limitations to the volume increase of loads and unloads.
The balance has a use of 1.15% and, as there are no workers specifically concerned with loading and unloading operations, taking two workers per shift, they are only occupied 13.5% of the time in loading and unloading operations. Given the low usage of the balance and how it can be operated independently, one of the ways to make the fixed asset profitable is to carry out external weighting by the company. This would give a small additional source of revenue without any negative impact on the unit.
For this to happen, no queues longer than two trucks are intended, thus clearing the company’s vehicles need to wait too long for other vehicles that are outside by the company’s activity. For the scale queue not to exceed two vehicles, the external weighting rate cannot exceed 1 weighting every 15 minutes. Even with the introduction of external weighting, the use of the scale does not exceed 6%.
In the scenario of an increase in company volume of transactions and consequently an increase in the volume of loading and unloading, the impact was also verified using simulation. Increasing the transactions volume by 300% will result in a maximum of 8-truck unloading queue. Although this is the longest waiting line, the longest waiting time is 6.5 hours of liquid loading and unloading. In this scenario, the expense on operators associated with loading and unloading is 23,600 € per year.
In the scenario where loading and unloading operations are only from 8am to 4pm, and the company has specific workers for this task, there are some important changes in the flow of vehicles. The maximum waiting time for a truck is 16 hours. In the case of product, the waiting time is still high with an average of 5h20m, but for other materials and liquids the average is 20m. In this fixed loading and unloading scenario, the company needs to have a park for 15 trucks waiting, which is the maximum foreseeable number with a 95% confidence level.
Both workers for loading and unloading are exaggerated because they are only working 7% of the time. If we only use 1 worker, the average time spent by the trucks in the factory goes from 1h10m to 1h30m, but the savings are significant if the workers are 100% affected to this operation.
This simulation case provides reliable information for making decisions about the loading and unloading process, but also increased revenues through unused capacity and optimized worker costs.