What Is a Continuous Test Stack

What Is a Continuous Test Stack

A continuous test stack connects every stage of manufacturing test into one integrated workflow: writing tests, deploying them to stations, executing on the production floor, collecting data, and analyzing results. Instead of disconnected tools at each stage, a continuous stack feeds data from production back into test development, creating a loop that improves test quality over time.

The Fragmented Stack Problem

Most manufacturing test operations look like this:

Every handoff between stages is manual. Data changes format. Context is lost. The feedback loop from production data back to test improvement takes weeks or months.

The Continuous Stack

A continuous test stack eliminates the handoffs:

The key difference: data flows automatically from execution to analysis, and insights flow back to development. There's no manual export step, no Excel processing, no emailed reports.

Components of a Continuous Test Stack

Prerequisites

• Python 3.10+
• OpenHTF installed (pip install openhtf)
• TofuPilot Python SDK installed (pip install tofupilot)
• Git for version control

Step 1: Write Tests in Git

Keep test scripts in a Git repository. Every change is tracked, reviewable, and reversible.

import openhtf as htf
from openhtf.util import units


@htf.measures(
    htf.Measurement("output_voltage_V")
    .in_range(minimum=4.9, maximum=5.1)
    .with_units(units.VOLT),
    htf.Measurement("current_draw_mA")
    .in_range(minimum=90, maximum=110)
    .with_units(units.MILLIAMPERE),
)
def phase_electrical(test):
    """Production electrical test."""
    test.measurements.output_voltage_V = 5.01
    test.measurements.current_draw_mA = 99.3

Step 2: Deploy with pip

Package your tests as a Python package. Stations install or update with one command.

pip install --upgrade your-test-package

This replaces the USB drive workflow. Every station runs the same version. Updates are traceable.

Step 3: Stream Results to TofuPilot

Connect the test to TofuPilot. Results flow automatically from every station to a central platform.

from tofupilot.openhtf import TofuPilot

test = htf.Test(phase_electrical)

with TofuPilot(test):
    test.execute(test_start=lambda: input("Scan serial: "))

Step 4: Close the Loop

The continuous part: use production data to improve tests.

Each action results in a code change in Git, a new deployment to stations, and the cycle continues. The stack is continuous because data flows in a loop, not a line.

Continuous Stack vs Point Solutions

The continuous stack approach trades some per-tool flexibility for end-to-end integration. The ROI comes from faster feedback loops: when you can go from "yield dropped" to "root cause identified" to "fix deployed" in hours instead of weeks, the investment pays for itself quickly.