Tera Calculation Reference System Specification Manual
Tera Calculation Reference System provides multi-dimensional analytical modeling for warehouse shipping transaction logs. Built around EIQ Analysis (Entry-Item-Quantity), it visualizes distribution center capacity sizing and operational efficiency.
💡 What is EIQ Analysis?
EIQ Analysis evaluates warehouse shipping transaction logs from three key dimensions: E (Entry: Order destination), I (Item: Product SKU), and Q (Quantity: Volume). It derives optimal warehouse layouts and picking methods.
1. System Architecture & Technical Stack
🎯 Primary Objectives
- Identify fulfillment center operational characteristics from shipping logs.
- Detect operational bottlenecks to improve labor productivity.
- Calculate optimized distribution center footprint capacity.
- Support data-driven executive decision-making.
🛠️ Technical Stack
Visual Basic .NET
Windows Forms
OLE DB
Microsoft Access Database
Chart Controls
Microsoft Excel Integration
2. System Module Structure
Primary Forms & User Interfaces
📊 Main Menu Form
TeraCalculation_ReferenceMenuForm
- Application entry point
- Navigates to EIQ Detailed Analytics
- Navigates to Traditional ABC Analytics
📈 EIQ Analytics Form
TeraCalculation4_ReferenceEIQForm
- Configured with 6 analytical tabs
- Data creation to chart visualization
- Includes custom data filtering
📋 Traditional ABC Analytics Form
TeraCalculation4_ReferenceTraditionalForm
- Total dataset aggregations
- Daily volume profiling
- Conventional ABC classification
3. Detailed Functional Modules
1) EIQ Data Creation Tab
Imports raw shipping transaction logs and builds the EIQ analytical database.
- Data Source: Microsoft Excel file (
ShippingData.xlsx)
- Primary Tables:
T000_ShippingData, T230_DailySummary, T130_TotalShippingSummary
-
Analytical Metrics:
- Case Shipments: Line count, piece count, case count, pallet count, volume (CBM), weight (kg)
- Piece Shipments: Line count, piece count, case conversion, pallet conversion
2) EIQ Curve Chart Tab
Visualizes shipping volume progression using time-series trend charts.
- Daily shipping volume progression
- Overlay display of multiple metrics
- Trend analysis and peak identification
3) EIQ Scatter Plot Tab
Renders scatter plots mapping relationships between Entries (customers) and Items (SKUs).
4) EIQ Data Table Tab
Renders detailed summary results in tabular grid formats.
5) EIQ Matrix Tab
Generates cross-tabulation heatmaps plotting customer destinations against product SKUs.
6) Custom Filter Tab
Executes multi-query filtering to isolate specific date ranges, customers, or quantity thresholds.
7) Piece-Picking Container Conversion Tab
Converts loose piece-picking order volumes into tote/container units.
4. Analytical Metrics Reference
| Category |
Metric Name |
Symbol |
Description |
| Case Shipping |
Lines |
C-Lines |
Total line item count for case shipments |
| Pieces |
C-Pcs |
Total piece count converted inside cases |
| Cases |
C-Cases |
Total master carton case count shipped |
| Pallets |
C-PL |
Total pallet load equivalent |
| Volume |
C-Vol |
Total gross volume in cubic meters (m³) |
| Weight |
C-Wt |
Total gross weight in kilograms (kg) |
| Piece Shipping |
Lines |
B-Lines |
Total line item count for loose piece picking |
| Pieces |
B-Pcs |
Total loose piece unit count |
| Case Equivalent |
B-Cases |
Loose pieces converted into case equivalents |
| Pallet Equivalent |
B-PL |
Loose pieces converted into pallet equivalents |
| Volume Equivalent |
B-Vol |
Total volume equivalent in cubic meters (m³) |
5. Database Architecture & Schema
Core Database Tables
| Table Name |
Description |
Application Purpose |
T000_ShippingData |
Raw Source Table |
Stores uncleaned raw shipping logs imported from Excel |
T130_TotalShippingSummary |
Master Summary Table |
Stores aggregated summary metrics across entire dataset |
T230_DailySummary |
Daily Summary Table |
Stores daily volume aggregations by shipping date |
T670_EIQScatterPlotRankData |
Rank Classification Table |
Stores rank classification data for scatter plot rendering |
📁 Database File: ShippingData.accdb
📄 Input Excel File: ShippingData.xlsx (Sheet1)
6. Traditional ABC Analytics Features
Traditional Calculation Capabilities
- Total dataset statistical summaries (total lines, items, customers)
- Daily volume trend charting and peak day identification
- Case shipping vs loose piece-picking comparative efficiency analysis
- Conventional ABC Pareto analysis for inventory velocity profiling
- Estimated carton dimension calculations from shipping metrics
7. System Requirements & Troubleshooting
Recommended Environment
- Display Resolution: 1920×1080 or higher
- Microsoft Excel: Excel 2010 or newer
- Microsoft Access: Access 2010 or ACE OLE DB 12.0 Driver
- .NET Framework: Version 4.5 or higher
⚠️ Important Operational Notes
- Processing datasets exceeding 100,000 rows may require extended processing time.
- Close input Excel files before running import routines.
- Avoid simultaneous multi-user locks on the Access database file.