Use Case with Alpha Transform and backend automation (Zenphi or Make, Zapier)

Workflow for measuring and sorting timber in the forest industry

Key aspects of data collection, data processing/decision-making, and physical logistics, with an overarching need for accuracy and efficiency.

Main aspects

1. Measurement Parameters:

• Diameter: At various points (e.g., butt, mid-point, top) to calculate volume and taper. This could be Diameter at Breast Height (DBH) for standing trees, or specific end diameters for felled logs.
• Length: Precise length of each timber piece.
• Species: Identification of the tree species, as this affects value, properties, and end-use.
• Quality Defects: Presence and type of defects (e.g., rot, cracks, excessive knots, sweep/bend, insect damage) that influence the grade and potential use (e.g., sawlog, pulpwood, veneer).
• Volume Calculation: The method used (e.g., Smalian's formula, Huber's formula, tapered cylinder formula) and if it's solid wood volume or includes bark.
• Weight: Often used for pulpwood or biomass, especially if timber is sold by weight.

2. Data Collection Methodologies:

• Handheld Device: Tablet or smartphone with specialised software that allow for digital input of measurements and observations. Logics for measuring the height of standing trees would be useful.

3. Sorting Criteria and Destination:

• Product Classes: Categorised timber (e.g., sawlogs, veneer logs, pulpwood, poles, biomass, firewood).
• Grades within Classes: Further sorting based on quality, size, and species within each product class (e.g., #1 Sawlog, #2 Sawlog).
• Customer Orders/Market Demand: Sorting decisions are heavily influenced by current orders and the highest value market for each timber type. Controlled by backend updates.
• Mill Specifications: Each receiving mill will have specific requirements for length, diameter, species, and defect tolerance. Controlled by backend.
• Physical Segregation: How and where the sorted timber is physically separated (e.g., different piles at the landing, designated trucks, specific bays at a mill). Controlled by backend.

4. Logistics and Flow:

• Where Measurement Occurs: At the stump (for standing inventory), at the felling site, at the landing (roadside), or at the mill. This dictates the technology and process flow and is set in the backend configuration.
• Transportation: How timber moves from the forest to the sorting point and then to various mills/destinations (skidders, forwarders, trucks). Current organisation updated via the backend.
• Tracking: How individual logs or bundles are tracked from origin to destination to maintain chain of custody, verify volume, and manage payments. This often involves tagging, barcode/QR codes, or digital manifests.

5. Workflow Stages (Typical):

• Pre-Harvest Inventory/Planning: Estimating timber volume and quality before felling.
• Felling & Delimbing: Trees are cut and branches removed.
• Bucking/Processing: Logs are cut to specific lengths based on market demand and quality. (This is where the initial measurement and sorting decisions are critical).
• Skidding/Forwarding: Moving logs from the felling site to a roadside landing.
• Landing Operations: Final sorting, scaling (measurement for payment/inventory), loading onto trucks.
• Transportation to Mill/Buyer: Delivery of sorted timber.
• Mill In-feed/Scaling: Re-measurement and quality check at the receiving mill.

6. Technology and Integration:

• Software Systems: What software is currently used for data capture, inventory management, sales orders, and tracking?
• Connectivity: How can data be transmitted (e.g., cellular, satellite, offline sync).
• Integration Points: How data will flow between different systems (e.g., from handheld device to office system, from harvester to central database, from Alpha to Zenphi).
• Reporting: What kind of reports are needed (e.g., daily production, inventory by species/grade, payment reports, yield analysis)?

7. Stakeholders and Business Rules:

• Foresters/Supervisors: Overseeing operations, making quality calls.
• Equipment Operators: Harvester, skidder, loader operators.
• Scaling Personnel: Individuals responsible for measuring and grading.
• Truckers: Transporting timber.
• Buyers/Mills: Receiving and verifying timber.
• Payment Rules: How producers/loggers are paid based on volume, weight, grade, etc.
• Regulatory Compliance: Environmental regulations, harvesting permits, sustainable forestry certifications.

By understanding these aspects we can design a robust workflow that leverages appropriate technologies (like Alpha for field data and Zenphi for backend automation) to optimise efficiency, accuracy, and profitability in timber operations.

The number of data points needed for Sorting Criteria and Destination depends heavily on the specific requirements of the sorting criteria and the level of detail needed for each timber piece. The typical data points per timber piece and how they contribute to sorting:

• Essential Data Points (usually per log/timber piece):

• Diameter: At least two points are often needed for accurate volume calculation (e.g., butt diameter and top diameter inside bark). More points might be needed for irregular logs or specific taper analysis.
• Length: A single, precise measurement per log.
• Species: One data point for species identification per log.
• Quality Defects: This can be multiple data points per log, depending on the number and type of defects present (e.g., presence of rot, size of knots, degree of sweep). Each significant defect would be a data point or a set of attributes.

• Derived Data Points (calculated from the above):

• Volume: Calculated from diameter(s) and length. This is a critical data point for sorting by product class and for payment.
• Grade: This is a classification derived from all the above measurements and defect assessments. It's often not a direct measurement but a decision point based on a set of rules.

How these satisfy Sorting Criteria and Destination:

• Product Classes (e.g., Sawlogs, Pulpwood, Veneer):

• Diameter and Length are primary determinants. A log below a certain diameter might automatically be classified as pulpwood, while larger, longer, and straighter logs are candidates for sawlogs or veneer.
• Species is critical as different species are used for different product classes (e.g., pine for lumber, specific hardwoods for veneer).
• Quality Defects are crucial. High-value product classes like veneer logs have very strict defect tolerances, while pulpwood can have significant defects.

• Grades within Classes:

• This is where the number and severity of defects become extremely important. A "#1 Sawlog" will have minimal defects, while a "#2" or "#3" will allow for more.
• Taper (derived from multiple diameter measurements) can also influence grading, especially for specific products.

• Customer Orders/Mill Specifications:

• These criteria directly translate into the specific ranges for diameter, length, species, and defect allowances that our collected data points must meet.

We generally need, for each timber piece:

• At least 2-3 diameter measurements (e.g., butt, mid, top) to characterise taper and calculate volume.
• 1 length measurement.
• 1 species identification.
• Multiple qualitative/quantitative assessments of defects.

The more precise and numerous the measurements, especially regarding defects and taper, the more accurately we can sort and maximise the value of each timber piece according to diverse customer and mill specifications. (Automated scanning systems often collect hundreds or thousands of diameter measurements along the length of a log to create a detailed 3D profile, enabling highly accurate volume calculations and defect mapping, which then feed directly into sophisticated sorting algorithms.)

Using Alpha Transform in the field for data collection and Zenphi for backend automations is an excellent complementary setup, leveraging the strengths of both platforms. Here's how we should best set this up:

I. Alpha Transform Setup (Field Data Collection)

1. Design The Transform Forms:

• Mimic Our Measurement Parameters: Create forms in Alpha Transform that precisely capture all the necessary timber measurement parameters (e.g., diameter points, length, species, defect types/severity). Use appropriate field types (numeric for measurements, dropdowns for species, checkboxes for defect presence).
• Incorporate Sorting Criteria Logic: While Zenphi will handle the complex automation, Transform can help guide the field user. We might include conditional fields based on initial inputs (e.g., if "rot" is checked, new fields appear to quantify rot severity).
• Offline Capability: Design forms knowing they'll be used offline. Alpha Transform is built for this. Data will sync automatically when connectivity is restored.
• User Experience (UX): Make the forms intuitive for field workers, minimising manual entry errors. Use features like barcode scanning for log IDs if applicable.
• GPS & Timestamping: Automatically capture location and time data with each submission, crucial for tracking timber origin.
• Photos/Media: Allow for photo attachments of defects or log conditions, which can be invaluable for quality control and verification in the Zenphi workflow.

2. Define Transform Data Output:

• Ensure the data collected in Transform forms is structured in a way that is easily consumable by Zenphi. This typically means designing forms that output clean, well-defined JSON. Each form submission will generate a JSON payload.

II. Connecting Alpha Transform to Zenphi (The Integration Point)

This is the crucial step where Alpha Transform hands off data to Zenphi.

1. Zenphi HTTP Trigger:

• In Zenphi, create a new flow and select the HTTP Trigger as its starting point.
• Zenphi will generate a unique endpoint URL for this flow after it's published. This URL is where Alpha Transform will send its data.
• Note down the URL and the authentication token (from "URL Using Authentication Header" or "URL Including Authorisation Token" in Zenphi's Invocation Tab). This token will be essential for secure communication.
• Define the variables in the Zenphi HTTP Trigger that we expect to receive from Alpha Transform's JSON payload (e.g., diameter, length, species, defects, timestamp, gps_location). Zenphi's Variables Tab will display a list of variables from the HTTP request, such as Http Body, Form Data, Query String Data, and Headers.

2. Alpha Transform's Data Submission Action:

• Configure our Alpha Transform application to submit the completed form data to Zenphi's HTTP Trigger endpoint. Alpha Transform's robust data integration capabilities allow it to send data to external APIs.
• You'll typically use an HTTP POST request from Alpha Transform to send the JSON payload to the Zenphi endpoint.
• Ensure the authentication token from Zenphi is included in the HTTP headers of the request sent from Alpha Transform (e.g., x-zenphi-httptriggertoken).
• Crucially, address CORS issues. If the Alpha Transform application is running in a browser environment (e.g., a web app), we will need to handle Cross-Origin Resource Sharing (CORS) errors. This usually means setting up a proxy server (e.g., using Node.js or PHP) on our domain that forwards the request to Zenphi's endpoint. Alpha Software's Xbasic can also facilitate server-side calls, bypassing client-side CORS issues if the call originates from the Alpha server.

III. Zenphi Setup (Backend Automations)

1. Process Received Data:

• Once the Zenphi flow is triggered by Alpha Transform's HTTP POST, the Http Body variable in Zenphi will contain the JSON data from Transform.
• Use Zenphi's "Parse JSON to Object" to extract individual data points (diameter, length, species, defects, etc.) from the Http Body.

2. Implement Timber Sorting Logic:

• This is where Zenphi shines. Use Zenphi's conditional logic (If/Then/Else branches) and lookup tables to apply our timber sorting criteria based on the extracted data.
• Examples:

• If (Length >= X AND Diameter >= Y AND Species = 'Oak' AND Defects = 'None'): Assign to "Veneer Log" category.
• Else If (Length >= A AND Diameter >= B AND Defects <= Z): Assign to "Sawlog Grade 1".
• Else: Assign to "Pulpwood".

• We can use formulas within Zenphi to calculate volume based on the received diameter and length.

3. Automate Actions Based on Sorting:

• Data Storage: Update Google Sheets, create entries in a Zenphi Table, or push data to a cloud database (e.g., Google Cloud SQL, Salesforce, external ERP via Zenphi connectors) with the sorted classification.
• Notifications: Send automated email notifications via Gmail to relevant stakeholders (e.g., "New Veneer Log identified - Log ID XYZ") or send messages to Google Chat/Slack.
• Reporting: Generate daily/weekly reports in Google Docs or Sheets summarizing timber intake by type, volume, and grade.
• Inventory Management: Update real-time inventory systems.
• Follow-up Tasks: Create tasks in Google Tasks or other project management tools for logistics teams to arrange specific transport for sorted timber.
• API Callback (Optional but Powerful): As mentioned in the Zenphi documentation, the flow could even call back to an Alpha-built web service to update a dashboard or a field worker's app in real-time with the sorting decision or further instructions. This would require Alpha to expose an incoming API endpoint via Xbasic web services.

IV. Monitoring and Maintenance:

• Zenphi Usage Tab: Monitor flow executions in Zenphi's Usage tab to track successful triggers and identify any errors.
• Conditional Run Tab: Use Zenphi's Conditional Run tab to set rules for when the flow should execute, preventing unnecessary runs (e.g., only run if specific form data is present).
• Error Handling: Implement error handling within Zenphi flows to catch issues with data processing or external integrations and send alerts.
• Testing: Thoroughly test the entire workflow with various scenarios (different timber sizes, defect combinations, offline/online transitions) to ensure accuracy and reliability.

This integrated approach leverages Alpha Transform's robust mobile data collection capabilities, especially in challenging environments, and combines it with Zenphi's powerful and flexible no-code automation engine for intelligent timber sorting and subsequent business processes.

Giving the logger the option to choose the measurement method directly addresses practical realities, as different timber types, cutting practices, or site conditions might favor one measuring method over another.

Here's how we can best implement this "choice of method" in our Alpha Transform to Zenphi workflow:

I. Alpha Transform Setup (Field Data Collection with Choice)

1. Introduce a "Measurement Method" Field:

• Add a dropdown or radio button field to our Alpha Transform form called, for example, "Volume Calculation Method."
• Options would be: "Smalian's Formula" and "Huber's Formula" (and potentially "Newton's Formula" if we want to offer that level of detail and require three diameter measurements).

2. Conditional Data Input Fields:

• This is crucial. Use Alpha Transform's conditional visibility features.
• If "Smalian's Formula" is selected: Show fields for Diameter_Butt and Diameter_Top (along with Log_Length).
• If "Huber's Formula" is selected: Show a field for Diameter_Midpoint (along with Log_Length).
• If "Newton's Formula" is selected: Show fields for Diameter_Butt, Diameter_Midpoint, and Diameter_Top (along with Log_Length).
• This ensures the logger only sees and inputs the data relevant to their chosen method, reducing clutter and potential errors.

3. Define Transform Data Output:

• Regardless of the chosen method, ensure our Transform form submits a JSON payload that includes:

• The Measurement_Method_Chosen (e.g., "Smalian's", "Huber's").
• Log_Length.
• All relevant diameter measurements collected (e.g., Diameter_Butt, Diameter_Top, Diameter_Midpoint), with null/empty values for those not used in the chosen method.

II. Connecting Alpha Transform to Zenphi (No Change)

• The connection remains the same: Alpha Transform sends an HTTP POST request with the JSON payload to our Zenphi HTTP Trigger endpoint, including the authentication token.
• Zenphi's HTTP Trigger will receive the Http Body containing all the data, including the chosen method and the relevant diameter measurements.

III. Zenphi Setup (Backend Automations with Conditional Logic)

1. Parse Received Data:

• Use Zenphi's "Parse JSON to Object" action to extract all submitted variables from the Http Body: Measurement_Method_Chosen, Log_Length, Diameter_Butt, Diameter_Top, Diameter_Midpoint.

2. Implement Conditional Volume Calculation:

• This is where Zenphi's conditional logic becomes very powerful. Use an "If/Else If" block to determine which formula to apply:
• If Measurement_Method_Chosen equals "Smalian's Formula":

• Perform Smalian's calculation using Diameter_Butt, Diameter_Top, and Log_Length.
• Formula: V=((π×(Diameter_Butt/2)2+π×(Diameter_Top/2)2)/2)×Log_Length (ensure units are consistent, e.g., convert cm to meters).

• Else If Measurement_Method_Chosen equals "Huber's Formula":

• Perform Huber's calculation using Diameter_Midpoint and Log_Length.
• Formula: V=π×(Diameter_Midpoint/2)2×Log_Length (ensure units are consistent).

• Else If Measurement_Method_Chosen equals "Newton's Formula" (if applicable):

• Perform Newton's calculation using Diameter_Butt, Diameter_Midpoint, Diameter_Top, and Log_Length.
• Formula: V=Log_Length/6×(π×(Diameter_Butt/2)2+4×π×(Diameter_Midpoint/2)2+π×(Diameter_Top/2)2) (ensure units are consistent).

3. Use Calculated Volume for Sorting:

• Store the calculated Volume in a Zenphi variable.
• Continue with our timber sorting logic (as discussed previously) using this Volume variable, along with species and defect data.

Benefits of this Approach:

• Flexibility for Loggers: Empowers field staff to choose the most practical or accurate method for the given situation.
• Data Integrity: Conditional fields in Alpha Transform ensure that only the necessary and correct diameter measurements are collected for the chosen method.
• Centralised Calculation: Zenphi handles the complex logic and calculations, ensuring consistency regardless of which field worker or method was used.
• Adaptability: The workflow can easily be adapted if new measurement methods are introduced or old ones are phased out, by simply updating the Transform form and Zenphi flow.

This setup intelligently combines Alpha Transform's flexible data collection with Zenphi's powerful automation capabilities, creating a robust and adaptable system for our forest industry client.