StanForD use & development. John Arlinger

Transcription

1 StanForD use & development. John Arlinger

2 Structure of presentation Introduction Use of StanForD in Sweden today Future

3 Supplying data Our production chain! Skotare We need StanForD information! Standardized Focus on machines data! We want to plan and control for maximum value and minumum costs!

4 What is StanForD? Standard for Forest machine Data and communication Focus on forest machines (CTL) International open de-facto standard used by all major manufacturers Financed by manufacturers & Swedish forest companies Date of birth: 1987 Two open meetings annually

5 Ingredients? Harvester instructions (incl products & species instructions) Forwarder instructions Harvested production Forwarded production Geographical information Operational monitoring Quality control (harvester measuring/forwarder scaling) User defined data (questionnaires)

6 Swedish use of StanForD? StanForD Harvested production Control bucking optimization Assortment volumes (m3sub) Forwarding Measuring Monitoring GIS Future Integration forest owner & industry Area 2,8 ha Volume 28,8 m3sub/ha Stems 418 stems/ha Basal area 5,7 m2/ha Mean stem vol 0,07 m3sub Strip roads 21% Saw log Pulpwood Rotten pulpwood Unclassified

7 Basic market model in Sweden Forest owner paid based on log measuring at industry Saw logs: a price per quality, length- & diameter classes Price list made to meet industrial needs and to optimize value for forest owner. Saw logs always cut for specific saw mill Affects the history of the standard and how it used!

8 Sveaskog - an example Harvesting instruction Controlling length/diam of saw logs Mix of products/assortments Updated 2-12 times per year Production data Logistics (transport & industry) Payments (contractor & forest owner) Measuring quality control Forest inventory Monitoring quality of measurement per harvester Geographical instruction Where to harvest and not to harvest Operational monitoring Machine KPI Team KPI Operator work times

9 Using StanForD in Sweden today! SDC is an organization: Owned by all forest owners associations, forest companies and industries Used by most companies for collecting and distributing data from CTL-machines

10 Harvester production Pri/hpr-files sent electronically to SDC once or twice day Summary of production data sent daily to forest companies (volumes per assortment & site) used for planning of logistics/transportation In some cases used for paying forest owner and contractor SDC has some web applications for detailed analyses (length/diameter distributions, manual cuts, bark functions etc)

11 Measuring accuracy Random control stems measured twice a day by operator Ktr/hqc-files sent electronically to SDC each day SDC s web application for detailed analyses of length and diameter accuracy (benchmarking etc)

12 Bucking instruction (Apt-file) Price matrixes constructed on regional level based on negotiations with industries Apt-file including all possible assortments Apt-file ed to contractor or downloaded from contactors web site Apt-file normally used on several consecutive sites (3 weeks 6 months) Operator selects what assortments to use on specific site. Will be distributed by SDC soon!

13 The future - StanForD 2010 Simpler, clearer & more flexible Get rid of old garbage Basic data registered in machine Calculations avoided in machine A more general format (XML) - easier to use

14 Instructions Forwarding object instruction (foi) Object identities Landing (location) New in StanForD Forwarding delivery instruction (fdi) Productgroups per mill Object geographical instruction (ogi) Map layers (photo, shpfiles) Presentation of map layers Ghd ld Apt-file in o StanForD Object instruction (oin) Object identities Logging company Forest owner etc Products Species group instruction (spi) Definition of species-groups DBH height Identiteties Bark function Product instruction (pin) Identities Lengths/Diameters Qualities Price matrix Distribution matrix

15 Reporting production Forwarded production (fpr) Products at specific landing? When unloaded? Prl Pri Object geographical report (ogr) Layers updated? When updated? Ghd Harvested production (hpr) Per harvested log: Product Length Diameter Stem no Per harvested stem: Stem no Species GPS-position Time of harvesting Total harvested production (thp) Total volume per product

16 Quality certification fqc New! fqc (auditor) Ktr hqc (auditor) hqc Stm/ktr Harvesting quality control (hqc) Log lengths Log diameters Measured by: Harvester Operator Auditor

17 Operational monitoring Drf Operational monitoring data (mom) Time, operator, object registered indivudally for: Processing Terrain travel Break Repaire Maintenance Travel to work Planning etc.

18 What does it mean to a user? Some examples. Flexible production control Reporting detailed production Operational monitoring

19 Flexible harvesting Changing industrial requirements Uppdating harvester fleet Shorter lead times (hours not weeks) 50% New product specification 25% 0% 3,82 m 4,05 m 5,13 m

20 Flexible harvesting Product instruction Object instruction incl product ref Forbid log 1. Change pulp assortm length 37 dm 2. New length distribution 3. New prices Start All machines at once! harvesting Production and monitoring reporting End harvesting Day Day Day HARVESTER TIME More flexible production control! Simple and more frequent reporting! No machine dialects!

21 Production data Yesterday Summerized data (eg log tally) Today/tomorrow Data registered per log and tree E.g.: log 3 Length 494 cm Diameter 207 mm Dbh 287 mm Coord. X,Y & Z Time 23:03:24 Automatic reporting per hour Advantages Agreggate any way we want Reconstruct trees Geographic information per tree

22 Volume after thinning (m 3 /ha) Manuell Manual reference referensmätning measurements Skördarprognos Prognosis based on harvester data Thinning stands

23 Operational monitoring. Work starts at 08:00 Processing Break Rep. Processing Terrain travel Maintenance Processing No work Start 09:10, 2800 sec Start 08:00, 1500 sec Production: 15 m3 Fuel: 8 liter Driven distance: 450 m Operator/Object/Shift Start 08:35, 1250 sec Transmission 1250 sec Re-fueling 900 sec Calibration 1900 sec

24 A week in the life of a harvester! Mid-sized harvester, week 50, Productivity, m 3 per h Mon Tue Wed Thu Fri Large stem volume Small stem volume

25 A week in the life of a harvester! Mid-sized harvester, week 50, 2011 Degree of technical utilization 100% 90% 80% 70% 60% 50% Mon Tue Wed Thu Fri What did Friday look like? Work Work Break Work 7:35 14:30 Planning strip roads!

26 Advantages Flexible production (control of harvesting) Detailed and flexible reporting per operator, hour, object etc Combining production, quality control and operational monitoring More efficient and profitable forestry!

27 My experiences Nothing happens without interest from users of data. First on the field sets the agenda. Takes time! No standard is 100% complete from start. A standard wins in the long run!

28 Data needs in the future? Forest company Production data (Hpr) Gis-data (Ogr) Pdf-follow-up Probably many more recievers Contractor in the (owner) future! Production data (Hpr) Monitoring (Mom) Pdf-follwo-up New requirements on systems: No conflict between reporting softwares Same files in different folders. Automatic (no need for operator actions) On-line (at least one 1 report per h) SDC Production data (Hpr) Quality control (Hqc) Most common in Sweden today! Manufacturer (owner) Monitoring (Mom) Other machine data