CASE STUDY / 01•Manufacturing systems•2024

PB Engine

Material Preparation Monitoring System

A production-readiness system that connects material planning, warehouse movement, and shop-floor visibility in one operational language.

Next.jsNode.jsMySQLFigma

32%

faster preparation cycle

4.8k

material records / month

1

shared source of truth

SYSTEM PREVIEW / 01
ops.dio.systems/pb-engine

01 / The Problem

Operational friction before the fix

Material preparation lived across spreadsheets, chats, and individual knowledge. Teams could see that a job was late, but not why — or who needed to act next.

02 / The Solution

Clear boundaries & status visibility

I mapped the physical preparation flow into a role-based monitoring system. Status logic, exception queues, and timeline views make the next operational decision visible before the delay compounds.

Key Operational Highlights

  • Translated warehouse and production rituals into a shared status model.
  • Designed an exception-first dashboard for supervisors, not just a report for management.
  • Reduced handover ambiguity with traceable ownership and event history.

03 / Code & System Architecture

How a business operates and how software responds.

The interesting part is rarely the syntax alone. It is the contract between the domain model, the UI, and the people who maintain the system.

File Tree Architecture

src/
domain/
readiness.ts
policies.ts
application/
overview-query.ts
ui/
OverviewScreen.tsx
Representative snippetNext.js
export async function getPreparationOverview(date: Date) {
  const jobs = await materialJobRepository
    .forDate(date)
    .withRelations(['items', 'owners']);

  return jobs.map((job) => ({
    ...job,
    health: calculateReadiness(job.items),
    nextAction: resolveNextAction(job),
  }));
}

The detail is intentional: readable boundaries make reliable collaboration possible.