Material Wastage in Manufacturing
What Percent of Your Raw Material Comes Out as Finished Goods?
Material Yield and Quality have a surprisingly high impact on the success or failure of your manufacturing venture. We look at relevant issues in some depth.
Yield is the percentage of raw material that ends up as good quality finished products
Rework involves fixing products that did not meet quality standards during the first pass
Scrap is the raw material that ends up as unusable, including failed reworks
Yield percentage is computed thus:
Material Yield % = (Good Output Weight ÷ Raw Material Input Weight) x 100
Rework is NOT Normal
It is easy to view rework as a normal part of production. It is NOT. Unless strictly controlled, it can become a big source of excess costs:
The rework item has already incurred the full cost of production during the first pass
Additional machine hour, labour, utility and factory overhead costs are incurred to fix issues with the quality-failed product
A dedicated rework area might also be set up if rework frequency is significant. This means extra expenditure on space and equipment.
When rework is on the main line, regular production has to wait for the line to clear
Reworking often means that deliveries to customers are delayed beyond promised dates, leading to possible order cancellations
Doing First Time Right
First-Time-Right
First-Time-Right (FTR) is a metric that tracks the percentage of products made perfectly on the very first try without needing fixes. FTR is the percentage of products that passed quality tests on the first run. It is calculated thus:
Units Passed First Inspection ÷ Total Units Started
If you start to produce 100 units and 98 units passed quality tests on the first run, your FTR is 98%. The remaining two units might be fixed through rework, or discarded as unrepairable scrap.
In addition to lowering operational costs, a high FTR also means less likelihood of the product being returned by customers as defective.
“Good” FTR varies across different manufacturing industries and for different use cases. For example, in Steel Wire Rope Manufacture:
It must be 99.5% for critical safety-tier ropes such as elevator cables, underground mining hoists, and aerospace cords, and
98.5% to 99.2% for general construction, heavy cranes, and shipping ropes
Startups frequently struggle with calibrating high-speed planetary stranding machines, and manage to achieve 95% to 97% during early stages.
Improving FTR
Certain steps can help even startups to achieve high FTR:
Poka-Yoke (Mistake-Proofing): Use physical guides, asymmetric pegs, or simple color-coded slots to design a process where workers literally cannot make a mistake during assembly
Golden Samples: Keep a perfectly manufactured product at every workstation so operators have a visual benchmark for quality.
Deploy Digital Work Instructions (Visual SOPs): Replace long text manuals with short, looped video screens or high-resolution photo steps
Short Feedback Loops: Don’t confine quality checks to the very end. Implement quick checks after every major assembly step to catch errors early.
A high FTR can minimise rework and scrap, thus increasing yield and decreasing costs. However, FTR cannot remedy yield problems related to product and process design or raw material suppliers. Let us look at these yield issues separately,
Why Scrap and Yield Need Separate Focus
A factory can have a perfect 100% FTR rate and still suffer from lower material yield and high scrap. This is because FTR only measures human and process mistakes during assembly. It completely misses three structural types of waste:
1. Design-Induced Scrap (Structural Waste)
The Problem: If a stamping machine punches a circular part out of a square metal sheet, the leftover corners are scrap. The operator did the job perfectly on the first try (100% FTR), but material was still wasted.
Separate Focus Needed: This requires Design for Manufacturing (DFM) or specialized CAM (Computer-Aided Manufacturing) software that uses spatial algorithms to tightly pack and arrange 2D or 3D part geometries onto a raw sheet of material.
2. Process-Inherent Waste (Engineering Waste)
The Problem: During machine purges, i.e. cleaning out leftover materials from internal parts before starting a new production run, the removed material is usually thrown away.
Separate Focus Needed: This requires SMED (Single-Minute Exchange of Die) to reduce changeover frequencies, or reusing removed materials after regrinding/recycling.
3. Supplier-Induced Yield Loss (Incoming Material Quality)
The Problem: If a startup receives a batch of raw plastic pellets contaminated with moisture, the finished parts will crack. The operators followed the SOP perfectly, but the yield dropped due to bad inputs.
Separate Focus Needed: This requires strict Supplier Quality Assurance (SQA) and incoming material testing protocols.
Minimizing Scrap
Scrap results from:
Poor machine calibration
Bad raw materials and
Human errors
Scrap is computed thus:
(Raw Material Input Weight - Good Output Weight) ÷ Raw Material Input Weight
Types of Scrap
Some scrap is accepted as normal. Examples include metal shavings and leftover materials during machine purges before a new setup.
However, there is also scrap (such as broken parts) that is avoidable by implementing preventive maintenance and better operator training
Case Study: Apex Automations (Electronic IoT Devices)
Background
Apex Automations is a startup that makes connected smart-home hubs. They produce 10,000 units per month. The retail price is ₹4,000 per unit, and the target production cost is ₹2,000 per unit (comprising ₹1,200 in raw materials and ₹800 in overhead/labor).
On paper, their monthly manufacturing budget is ₹2,00,00,000 (2 Crore). However, they are consistently over budget. A consultant stepped in to analyze the cumulative impact of material wastage.
Step 1: Direct Scrap (The Obvious Waste)
During the plastic injection molding phase for the device casing, the startup experienced a 5% scrap rate due to improper machine calibration and raw material trimming.
The Impact: To get 10,00,000 usable casings, they actually had to feed raw materials for 10,500 units into the machines.
The Cost: 500 units worth of plastic material wasted.
Direct Scrap Loss = 500 x ₹1,200 = ₹6,00,000
Step 2: Indirect Setup Waste (The Invisible Waste)
Every time the factory switches production colors or reboots the machines after a weekend shutdown, they run "purge cycles." The purged material cannot be used for final products. This accounted for 2% of total monthly material.
The Impact: Material equivalent to 200 units was systematically thrown away during changeovers.
The Cost: 200 units worth of raw material destroyed.
Indirect Setup Waste = 200 x ₹1,200 = ₹2,40,000
Step 3: Rework Waste & Low First-Time-Right (The Compounding Wave)
The remaining units moved to circuit board (PCB) assembly. Because of a low First-Time-Right (FTR) rate of 88%, 1,200 units failed the initial quality check.
The startup decided to rework these units instead of scrapping them. However, reworking a product introduces a secondary wave of material and labor waste:
Rework Scrap: During the desoldering process, 10% of the 1,200 faulty boards (120 units) were accidentally burned and completely ruined.
120 units × ₹1,200 material cost = ₹1,44,000
Added Overhead: The remaining 1,080 faulty units required double the labor, extra solder, and additional testing energy (costing an extra ₹400 per unit in rework labor/overhead).
1,080 units × ₹400 extra cost = ₹4,32,000
The Cumulative Financial Summary
Waste Type Physical Units Lost / Impacted Financial Impact (₹)
Direct Scrap (Molding) 500 units of material lost ₹6,00,000
Indirect Waste (Setup/Purges) 200 units of material lost ₹2,40,000
Rework Scrap (Burned Boards) 120 units of material lost ₹1,44,000
Rework Overhead (Extra Labor) 1,080 units requiring double work ₹4,32,000
TOTAL MONTHLY LOSS Equivalent to 1,900 units disrupted ₹14,16,000
The Consultant's Verdict
The startup believed they had a "small 5% scrap issue." In reality, the cumulative effect of direct scrap, setup purges, low FTR, and rework errors drained ₹14.16 Lakhs per month. This slashed their expected startup profit margins by over 7% and severely throttled their monthly cash runway.
Recommendations
1. Patching Upstream Leaks: Direct Scrap & Setup Waste
The goal here is to optimize machine uptime and prevent material from being thrown away before assembly even begins.
Implement SMED (Single-Minute Exchange of Die):
The Action: Standardize the machine changeover process to reduce setup times.
The Impact: Minimizes the number of "purge cycles" needed to clear the barrels, cutting down the 2% Indirect Setup Waste.
Establish a "First-Piece Inspection" Protocol:
The Action: Operators must check and sign off on the very first unit produced after a machine calibration before starting full production.
The Impact: Stops the machine from running hundreds of bad parts continuously, directly tackling the 5% Direct Scrap leak.
Regrind and Recycle (Where Applicable):
The Action: Introduce a granulator next to the injection molding machine to grind clean plastic runners and scraps back into pellets.
The Impact: Reintroduces waste material straight back into the hopper, recovering raw material costs instantly.
2. Patching Midstream Leaks: Low First-Time-Right (FTR)
The goal here is to build quality into the process so errors are caught or prevented at the workstation.
Deploy Digital Work Instructions (Visual SOPs):
The Action: Replace long text manuals with short, looped video screens or high-resolution photo steps at the PCB assembly benches.
The Impact: Reduces human assembly errors, instantly pushing the 88% FTR rate closer to the 95%+ industry benchmark.
Source-Side Inspection (Poka-Yoke):
The Action: Use physical alignment pins or fixtures on the assembly jigs so components can only fit in the exact, correct orientation.
The Impact: Prevents workers from soldering boards backward, eliminating inspection failures before they happen.
3. Patching Downstream Leaks: Rework Material and Overhead Losses
The goal here is to make the rework process safe, controlled, and standardized so parts do not get destroyed twice.
Designate a Specialized Rework Zone:
The Action: Remove rework tasks from the main production line. Create a dedicated station equipped with high-grade desoldering tools and static-free mats.
The Impact: Prevents secondary damage (like burning the board), completely erasing the 10% Rework Scrap leak.
Create a Standard "Rework SOP":
The Action: Treat rework like a primary manufacturing process with its own step-by-step instructions, rather than letting technicians "wing it."
The Impact: Lowers the time spent per unit, heavily reducing the ₹432,000 Rework Overhead labor cost.
Hourly Quality Feedback Loops:
The Action: If a specific error occurs three times in an hour, the rework technician must immediately notify the upstream assembly operator to fix the root cause.
The Impact: Stops a systematic error from repeating across thousands of units.
Conclusion
We looked at factors that determine how much of the raw material ends up as finished product, i.e. yield. Yield is affected by both unavoidable and avoidable scrap.
Implementing First Time Right (FTR) was reviewed. We noted that while FTR can reduce rework and some scrap, additional focus was needed to increase yield and minimise scrap.
A case study demonstrated how these concepts work in a real life environment. We ended by looking at the specific actions needed to stop the high material wastage in this case..