Data clearly shows that improving loading efficiency for the Skogger will greatly improve productivity

Using good data to support your forest operations

Stellenbosch University in conjunction with the South African Forest industry has developed a robust and internationally aligned Time Study Standard and Data Repository Protocol for use by forest managers, practitioners/contractors and researchers. As part of ongoing support for forest operations The Forest Operations Productivity Initiative includes several machine and systems costing models which will also soon include silvicultural operations as part of the overall forest productivity package. The objectives of these efforts are to improve, if not optimise, silviculture and timber harvesting operations in the face of ever increasing international competition, and to provide planning tools to not only the South African Forest Industry but to international partners as well.

The Time Study Standard and Data Repository Protocol provides a common and standard methodology for planning, implementing, analyzing, and sharing work study projects. Through use of this standardised approach, data gained from different studies, by different people trained in this protocol, can be compared, pooled and analyzed without reserve. Now, individual smaller studies can contribute to larger data driven analysis regimes, for the benefit of both large and small users. Documentation of the standards and protocols from this initiative are collected and shared on the website.

The establishment and implementation of this standard aligns the Forest Industry with the international forest operations community and assists with the ‘modernization’ of local forest operations. Forest Operations Productivity Initiative data is collected by partner organizations and individuals. Each study is reviewed and confirmed to meet rigorous baseline standards, with the raw time and volume data results shared without identifying source information. No data in the database is linked to any particular company or concern. While these data are further analyzed by the organizations that originally collected the data, data shared with the Forest Operations Productivity Initiative does not have any analysis of the data included in the repository. Individual users are encouraged to use any and all of these data within their own context.

Additionally, no costing results or data are included in the repository to avoid any sharing of an organization’s financial data.
In brief is a resource which provides:
• Comprehensive guidelines and assistance in completing a time study.
• Decision support tool to help select the appropriate time study technique for different study objectives.
• Time study background information forms and data collection sheets.
• Statistical analysis decision support tool and analysis procedures for different study objectives.
• Access to and instructions for various android applications including ‘The Time Study App’ and the ‘Decimal-minute Stopwatch App’.
• Tutorials on analyzing time study app data as well as providing training courses on planning and conducting time studies.
• Exposure to the Time Concept protocol developed by International Union of Forest Research Originations (IUFRO), which is the basis of all time studies and work allocation in forest operations worldwide.
• Productivity data repository to store study information which provides detailed diagnostics on the various elements affecting performance.
• Access to the South African forest machine and systems costing model, developed in accordance to international costings standards.
• Access to a Cost Action single machine costing model.

Projects using time study standards
The following two examples illustrate how data driven information currently included in the Forest Operations Productivity Initiative data repository, which is available to members of the initiative, can be used to analyse and better understand their operations.

The first example, shown in the figure below, illustrates a productivity model that predicts the productivity of a hybrid harvester, used in pine on the Mpumalanga escarpment based on different DBH sized trees. This model can support decision making related to matching machines and attachments to conditions, and for machine and systems costing.

The second example, shown in the following figure, illustrates the impact of loading time on the productivity of a Skogger. The coarse loading time data summarized in this plot, clearly show that improving loading efficiency for this machine will greatly improve productivity. With these study results, supervisors can implement operator training, equipment modifications, or other adjustments to existing operations to realize major changes in productivity.

Although the two examples above are potentially derived from limited data sets, this is where the benefit of the data repository intuitive becomes evident. Instead of relying only on one (potentially small) data set, a search of the repository may reveal other datasets of a similar machine, but with other terrain and resource type for example, which can be combined to provide more in-depth information to the benefit of your organization. So the benefit of extended contributions becomes evident.

The future of the project
Even though there is considerable data already contained in the Forest Operations Productivity Initiative repository, the coverage of all forest operations, machines, and terrain and resource types will require significant efforts. This project has taken the first steps and is building a resource that will be a valuable tool for participating industry partners.

Data collection requires some technical skills and practice that the Forest Operations Productivity Initiative team can help with. Training sessions are provided to individuals from interested organizations once a year. This comprehensive training is sufficient to equip attendees with the knowledge and skills necessary to implement basic time study projects and start developing into their organization’s time study specialists.

If an organization does not have the ability to develop their own in-house time study personnel, Stellenbosch University may have access to a set of trained students and researchers that can do this work independently and supply professional reports with results. Additionally, there are a few trained contractors that may also be available to provide time study data collection and analysis services that follow the establish standards and can be included in this project.

Hence, we encourage organizations not yet partners in the Forest Operations Productivity Initiative efforts to make contact with us to explore your involvement.

The Forest Operations Productivity team:
Simon Ackerman –
Ben Spong –
Marius Terblanche –
Pierre Ackerman –

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