Three monitoring points for continuous improvement of forestry processes

In the long term, the absence of good management can completely harm any business development. For this reason, in forestry operations — which take years to complete — keeping management up to date is essential to ensure the quality of processes. Optimised planning, efficient execution, precise machine controls and automated work flow are some of the results, which in turn enable increased productivity and profit.

“A major concern of companies in the sector is continuous improvement. They look for technology suppliers to understand what is happening on the farms and what can be improved, either to guarantee more satisfactory results or to eliminate unnecessary costs”, comments Claudia Garcia, Manager of Forestry Contracts at the Hexagon’s Agriculture division, which develops digital solutions for agricultural and forestry operations.

Today, through sensors, hardware and software installed in forestry machinery, managers are able to monitor each operation step and rely on various data and analyses that help in making strategic decisions and solving problems. Check out three factors that can be monitored to promote continuous improvement in forestry processes.

1 - Worked area
An important indicator obtained through monitoring is the worked area status. Having the total operation area and records of the work performed, it is possible knowing what was, in fact, the space percentage in which the planned activity was performed, whether it is soil preparation, fertilisation, planting, or any other.

“In general, management considers the work execution in the total area. However, due to limited conditions, such as the presence of isolated native trees, rocky outcrops or wood cemeteries, most of the time the actual operation area is smaller than planned.  At a client where we recently carried out a proof of concept, we have analysed more than 5,400 plots with an area of up to 50 ha, and the subsoiling operation had an average status equal to 84% of the plots area”, explains Claudia.

The manager also reinforces that the manual survey of non-productive spaces by a georeferencing team, in addition to generating a higher cost for the team to travel to the field, is often unfeasible due to the high effort required, and subjects the employees to the inherent risks of that environment.

This way, monitoring the worked area allows a more precise control of forestry activities and, consequently, adjustments in management issues, such as payments for services and the write-off of inputs. Having this productive site status also helps in planning subsequent actions, such as the quantity of inputs and seedlings sized for the effective area for planting, and minimises errors in estimating the wood volume in forest inventories.

2 - Operating times
Details on operating times are another great contribution of monitoring technologies to forestry management. These tools provide a second-by-second measurement of what is being done on the farm—whether the machine is stopped, fertilising, subsoiling, and so on. 

So, it is possible verifying exactly the total productive and unproductive time of the operations in different levels of grouping: yield by machine, by operator or by geospatial classification (field, farm or unit), for example. About 10 years ago, to execute the subsoiling activity, only 29% of the total time monitored corresponded to the time in which subsoiling actually took place, the other times being unproductive or auxiliary to production. With the evolution of monitoring and good practices adopted by management, currently the productive time for this operation has increased by 45%. This results in asset optimisation and consequent cost reduction with the intelligent use of resources.

“The gains for the manager from the good use of this data are many, as he is able to know where the bottlenecks are in the operation and what can be improved”, comments Claudia. The systems can also raise reasons for unproductive times, such as the need for corrective maintenance, lack of input for supply, unfavorable weather conditions, among others.

Based on this, it is possible acting on the identified information, whether in the field of supply logistics, negotiating with service providers, creating policies to reward operators for productivity or improving the preventive and corrective maintenance strategy of machines and implements. 

3 - Application of inputs
Other example of data analysed in operations is the total inputs applied. Here comes the control and monitoring of activities such as fertilizers and correctives application, herbicide mixture, ant bait, among other operations carried out in the forest implementation and maintenance.  

With this value in hand, it is possible analyzing how the operation was carried out, whether there was an overdose or underdosage, what was the percentage of the deviation, whether it will be necessary to carry out any reapplication action, and so on. As the data are georeferenced, information are available on the exact areas that failed in the application, which facilitates the performance of new activities to finalize or improve the application of inputs previously carried out.

Monitoring can also be important for managers to assess the importance of investing in a controller. This technology type allows the released input dosage to vary according to machine speed oscillation, resulting in a homogeneous application and very close to the recommendation in the entire forest area. “An estimate based on the real analysis of a customer's scenario is that, in a conventional system, in an area of 42.19 ha, the deviation in the dosage applied with the control system was 0.77% in relation to the recommendation (300kg /ha)”, reinforces the Forestry Contracts Manager of Hexagon's Agriculture division.

In this same scenario, considering the input application with a conventional system where there is no input flow control according to oscillations in the machine's displacement speed, the deviation was -10.08%. This is because the conventional system was calibrated for a constant speed of 4.0 km/h and this machine's real average speed was 4.70 km/h, that is, it moved faster, consequently the dosage is lower since the implement without the controller it was calibrated for another travel speed. With the available data, complementary actions such as stock reduction of inputs, control of service orders and payments to third parties can be carried out automatically.