Success Case - Foundry
How Harumi Made Molding Planning More Predictable and Integrated with Melting
The Challenge: Planning Without Visibility into Production or Yard Capacity
Overview
Before Harumi, Molding followed the Melting schedule without a predefined sequence that accounted for production cycles, setups, processing times, production pace, and future staging area occupancy.
To decide which work order to run, the operator had to physically check the available materials and resources. In addition to taking time, this routine required walking around the facility and performing repeated checks, increasing the operational effort and fatigue over the course of the shift.
When inputs were unavailable or delays occurred, the operator moved on to the next work order. Without a forecast of when each load would be ready or how much space would be available, the melting sequence had to be changed every day.
The team spent approximately one hour per day reviewing the schedule. The lack of consolidated metrics also made it difficult to understand production capacity and efficiency losses. As a result, Production Planning and Control, supervisors, and operators worked primarily in a reactive manner.
The Solution Integrated Planning with Harumi
Harumi turns the Melting schedule into a detailed Molding plan, processed in approximately one minute.
The platform:
sequences work orders within melting groups;
sets planned start and finish times;
accounts for setups, changeovers, and processing times;
projects staging area occupancy;
calculates the time buffer between the completion of each work order and its melting time;
flags risks of delay, overload, and insufficient capacity;
compares different production configurations;
supports resequencing when the original plan is not feasible;
consolidates the information needed for decision-making, reducing reliance on repeated physical checks.
Simulation and Process Knowledge
The project also made it possible to structure metrics such as OEE, processing and setup times, resource utilization, idle time, takt time, and staging area capacity.
At Rollover, for example, the simulation determines the takt time and the appropriate number of positions or models produced in parallel. Each configuration is evaluated based on its effect on work order completion, resource utilization, and staging area occupancy.
This makes it possible to balance the pace of Molding with demand from Melting, avoiding both early production, which can overload the staging area, and late completion of loads.
Delivery
Completed work orders and delay tracking across the planning horizon
Capacity
Resource utilization, available capacity, and shift requirements
Efficiency
OEE, idle time, and cycles produced per hour
Setup
Number and duration of changeovers
Staging area
Average and maximum occupancy, available positions, and peak time
Synchronization
Time buffer between work order completion and melting time
Production pace
Takt time and number of positions or models running in parallel
Planning
Processing time and plan-to-actual adherence
The output files complement the dashboard with information about work orders approaching their melting deadline and work orders outside the planning horizon. Together, this information helps identify bottlenecks, monitor resource use, and quickly assess whether the plan can meet demand. It also reduces the time spent searching for and manually consolidating information, allowing the operator to focus on executing and monitoring the process.
Support for Management Decisions
In one real case, the simulation showed that the available capacity would not be sufficient to meet demand. With this information, management identified in advance the need to add a production shift.
The project therefore goes beyond work order sequencing. It also supports decisions about capacity, machines, shifts, and staffing before a lack of resources disrupts the schedule.
From Reaction to Anticipation
Before
With Harumi
Decisions made during operations
Planning completed in advance
About one hour of manual review each day
Plan processed in approximately one minute
Operator physically checked availability
Consolidated information supports decision-making
Repeated walking and checks
Less operational effort required to review the schedule
Future staging area occupancy unknown
Occupancy projected across the planning horizon
Metrics not clearly structured
Efficiency, time, and capacity measured
Production pace based mainly on experience
Takt time and parallel operations evaluated through simulation
Bottlenecks identified after affecting operations
Risks flagged in advance
Resource needs identified during execution
Capacity, shifts, and staffing evaluated in advance
Information scattered across departments
Management dashboard provides an integrated view
Molding and Melting planned separately
Schedules synchronized
Case Study Summary
Harumi turned Molding sequencing into an operational and management planning tool. By simulating the production pace, resource capacity, work order times, and staging area occupancy, the platform increased predictability, integrated Molding and Melting, and created a quantitative basis for decisions about capacity, shifts, and priorities.
Centralizing the information also reduced reliance on repeated physical checks, lowering the operational effort required to review the schedule and freeing the operator to focus on higher-value activities. In one real case, this visibility made it possible to anticipate the need for an additional shift to meet demand.
-38%
Reduction in late jobs.
AFM significantly increased the number of orders delivered on time.
-11%
Reduction in total setup time.
In practice, this meant more output with the same resources, without additional investment.
-100%
Reduction in manual planning time.
No more spreadsheets.
