Strategies to evaluate how well a manufacturing system has worked.

Quantity Production – Evaluating Manufacturing Systems

Learning Objective

Students will be able to select, apply and interpret a range of quantitative and qualitative strategies to evaluate how well a manufacturing system has performed in quantity production, and to propose realistic, sustainable improvements that meet the requirements of the Cambridge International AS & A Level Design & Technology (9705) syllabus.

1. Production Scales & Their Evaluation (Topic 15 – Quantity Production)

The scale of production determines the type of manufacturing specification required and the evaluation metrics that are most relevant.

Production Scale	Typical Characteristics	Key Evaluation Metrics
One‑off (custom)	Single piece, high design flexibility, long set‑up, low repeatability.	Set‑up time, lead‑time, cost per unit, defect‑rate, customer satisfaction.
Batch production	Limited run (dozens to thousands), repeated set‑ups, change‑over between batches.	Set‑up & change‑over time, batch yield, OEE (availability focus), waste ratio, cost per batch.
Mass (continuous) production	Very high volume, minimal set‑up, highly automated, excellent repeatability.	OEE, throughput, production efficiency, scrap/re‑work rate, cost per unit, waste ratio.

2. Manufacturing Specification for Quantity Production

A manufacturing specification translates the design brief into clear, measurable production requirements. It must contain:

• Product dimensions & tolerances (e.g., ±0.1 mm).
• Material grade, heat‑treatment and surface‑finish requirements.
• Required processes and their sequence (e.g., stamping → CNC machining → anodising).
• Target production rate and total order quantity.
• Cost ceiling per unit and allowable waste limits.
• Quality checks & acceptance criteria (inspection points, maximum defect level).
• Health & safety, environmental and regulatory constraints (e.g., ISO 14001, REACH).

During evaluation each item is cross‑checked against shop‑floor data to confirm whether the specification has been met.

3. Commercial Manufacturing Systems (Topic 15)

System	Core Principle	Typical Application	Advantages	Disadvantages	Evaluation Focus
Just‑In‑Time (JIT)	Produce only what is needed, when it is needed.	Automotive assembly, consumer electronics.	Low inventory carrying cost, fast response to demand changes.	Vulnerability to supply‑chain disruptions, requires reliable suppliers.	Inventory turns, lead‑time, availability, supplier reliability.
Computer Integrated Manufacturing (CIM)	Full integration of design, planning, production and control via CAD/CAM/ERP.	Complex, high‑mix, medium‑volume factories.	Improved data consistency, rapid design‑to‑production, better scheduling.	High capital cost, dependence on software reliability.	Data integrity, OEE, cycle‑time variance, information‑flow errors.
Cellular Production	Workstations arranged in a cell to complete a family of parts.	Batch production of similar components (e.g., gearbox parts).	Reduced material handling, shorter lead‑times, higher operator skill.	Limited flexibility for very large families, possible imbalance between stations.	Change‑over time, throughput, intra‑cell quality, utilisation.
Concurrent Engineering	Parallel development of design and manufacturing processes.	New‑product development programmes.	Reduced time‑to‑market, early identification of manufacturability issues.	Requires strong cross‑functional communication, risk of scope creep.	Time‑to‑market, design‑for‑manufacturability (DFM) metrics, early‑stage cost estimates.
Flexible Manufacturing System (FMS)	Automated, re‑configurable equipment capable of handling varied part families.	High‑mix, low‑to‑medium volume environments (e.g., aerospace components).	High equipment utilisation, quick change‑over, ability to respond to demand variability.	Complex control systems, higher maintenance requirements.	Machine utilisation, change‑over flexibility, OEE, downtime analysis.

4. Key Evaluation Strategies

• Compare actual output with planned output (efficiency).
• Analyse production efficiency, utilisation and availability.
• Identify and quantify both planned and unplanned downtime.
• Calculate quality‑related losses (defects, re‑work, scrap).
• Determine Overall Equipment Effectiveness (OEE).
• Review cost per unit, waste ratio and broader environmental impact.
• Apply quality‑system tools (Pareto, Fishbone/Ishikawa, 5 Why, SPC charts) as part of the evaluation to locate root causes.
• Benchmark each indicator against the targets set in the manufacturing specification and against historic or industry‑standard values.

5. Performance Indicators

Indicator	Definition	Typical Formula
Planned Output (P)	Number of units the system is scheduled to produce in a given period.	\(P = \text{Planned rate}\times\text{Available time}\)
Actual Good Output (A)	Number of good (conforming) units produced.	\(A = \text{Total units produced} - \text{Defective units}\)
Production Efficiency	How close the system comes to its planned output.	\(\text{Efficiency (\%)} = \dfrac{A}{P}\times100\)
Availability	Proportion of scheduled time that the equipment is ready to operate.	\(\text{Availability (\%)} = \dfrac{\text{Operating Time}}{\text{Planned Production Time}}\times100\)
Performance Rate	Speed of production relative to the ideal cycle time.	\(\text{Performance (\%)} = \dfrac{\text{Ideal Cycle Time}\times A}{\text{Operating Time}}\times100\)
Quality Rate	Proportion of good units out of total produced.	\(\text{Quality (\%)} = \dfrac{A}{\text{Total Units Produced}}\times100\)
Overall Equipment Effectiveness (OEE)	Combined measure of availability, performance and quality.	\(\text{OEE (\%)} = \text{Availability}\times\text{Performance}\times\text{Quality}\) (expressed as decimals)
Cost per Unit	Total production cost divided by the number of good units.	\(\text{Cost per Unit} = \dfrac{\text{Total Cost}}{A}\)
Waste Ratio	Material waste expressed as a percentage of material input.	\(\text{Waste Ratio (\%)} = \dfrac{\text{Material Waste}}{\text{Material Input}}\times100\)
Set‑up / Change‑over Time	Time required to prepare equipment for a new batch or product.	\(\text{Set‑up Time} = \text{Start‑up duration (min)}\)
Scrap / Re‑work Rate	Proportion of units that must be discarded or re‑processed.	\(\text{Scrap Rate (\%)} = \dfrac{\text{Scrap units}}{\text{Total units produced}}\times100\)

Note: After each indicator is calculated, compare it with the target values stated in the manufacturing specification and with previous periods or industry benchmarks.

6. Mapping Processing Methods to Indicators & Sustainability

Processing Method	Typical Strengths	Key Indicators to Monitor	Environmental / Sustainability Considerations
CNC Machining (subtractive)	High dimensional accuracy, repeatability.	OEE, scrap rate, tool‑wear cost, cycle‑time variance.	Coolant usage, energy consumption, chip recycling.
Injection Moulding (plastic)	Very fast cycle, low per‑part cost at high volume.	Waste ratio (gate/flash), cycle‑time, quality (shrinkage, voids), OEE.	Polymer choice (recyclable vs. virgin), mould wear, energy per shot.
Stamping / Press Forming (metal)	High speed, low material waste for sheet metal.	Set‑up time, waste ratio, scrap rate, availability.	Lubricant management, scrap metal recycling, noise.
Laser Cutting / Water‑jet (sheet cutting)	Flexibility for small batches, low set‑up.	Utilisation, waste ratio (kerf loss), edge quality.	Energy intensity (laser), water consumption (jet), gas emissions.
3D Printing (additive)	Complex geometry, low tooling cost.	Build time, material waste (support material), quality (porosity), cost per unit.	Material recyclability (e.g., PLA), powder handling, energy per build.
Joining (welding, brazing, adhesives)	Creates assemblies from sub‑components.	Defect rate (porosity, cracks), re‑work cost, cycle‑time, safety compliance.	Fume extraction, consumable waste, choice of low‑VOC adhesives.

7. Quality Systems, Standards & Tools (Topic 17)

• Quality Assurance (QA) – systematic activities (process design, documentation, audits) that ensure the production system can consistently meet specifications.
• Quality Control (QC) – operational techniques (inspection, testing, statistical process control) that monitor output against the specification.
• Relevant International Standards
  • ISO 9001 – Quality management systems; provides the framework for QA/QC documentation and continual improvement.
  • ISO 14001 – Environmental management; links waste ratio, energy use and emissions to sustainability targets.
• Total Quality Management (TQM) – organisation‑wide philosophy that integrates QA, QC, employee involvement and customer focus to achieve zero‑defect production.
• Key QA/QC Tools for Evaluation
  • Statistical Process Control (SPC) charts – monitor variation in dimensions, cycle times, etc.
  • Pareto analysis – identify the most significant sources of loss (e.g., 80 % of downtime caused by 20 % of failure modes).
  • Fishbone (Ishikawa) diagram – structure cause‑and‑effect investigations.
  • 5 Why questioning – drill down to the root cause.
• Data from QA/QC (inspection pass‑rate, SPC limits, non‑conformance reports) feed directly into the Quality Rate, Scrap Rate and OEE calculations.

8. Step‑by‑Step Evaluation Process

1. Collect data
   • Manufacturing specification & production schedule.
   • Machine logs (run time, breakdowns, set‑up/change‑over times).
   • Quality inspection records (defects, re‑work, scrap).
   • Material usage, waste and recycling records.
   • Cost accounting (labour, energy, tool wear, overhead).
   • QA/QC documentation (SPC charts, audit reports, non‑conformance logs).
2. Calculate primary indicators – Efficiency, Availability, Performance, Quality, Set‑up time, Scrap rate.
3. Combine to obtain OEE – multiply Availability, Performance and Quality (expressed as decimals).
4. Analyse economic & environmental performance – Cost per unit, Waste ratio, Energy per part, carbon footprint.
5. Benchmark
   • Compare each indicator with the target values set in the manufacturing specification.
   • Contrast with previous periods, similar product lines, or industry standards.
6. Identify root causes of shortfalls using Pareto, Fishbone, 5 Why or SPC trend analysis.
7. Formulate realistic improvement actions – actions must be feasible within the constraints of cost, time, resources, health & safety, and sustainability (e.g., SMED to reduce set‑up, preventive maintenance schedule, optimisation of cutting parameters, operator training).
8. Implement actions & monitor – repeat the evaluation cycle to verify that the improvements have moved the indicators towards the specification targets.

9. Example Calculation (CNC Machining Centre)

Scenario: A CNC machining centre is scheduled to produce 10 000 parts in an 8‑hour shift.

• Operating time (excluding breakdowns & set‑up): 6.5 h
• Total units produced: 9 800
• Defective units: 200
• Ideal cycle time: 2 s / part
• Total production cost: £24 500
• Material waste: 150 kg (material input 5 000 kg)
• Energy consumption: 1 200 kWh (≈0.125 kWh/part)

Calculations:

$$\text{Planned Output } P = \frac{8\text{ h}\times3600\text{ s/h}}{2\text{ s}} = 14\,400\text{ parts}$$ $$\text{Actual Good Output } A = 9\,800 - 200 = 9\,600\text{ parts}$$ $$\text{Efficiency} = \frac{9\,600}{14\,400}\times100 = 66.7\%$$ $$\text{Availability} = \frac{6.5\text{ h}}{8\text{ h}}\times100 = 81.3\%$$ $$\text{Performance} = \frac{2\text{ s}\times9\,600}{6.5\text{ h}\times3600\text{ s/h}}\times100 = 81.0\%$$ $$\text{Quality} = \frac{9\,600}{9\,800}\times100 = 98.0\%$$ $$\text{OEE} = 0.667\times0.813\times0.980 = 0.531\;(53.1\%)$$ $$\text{Cost per Unit} = \frac{£24\,500}{9\,600} = £2.55$$ $$\text{Waste Ratio} = \frac{150}{5\,000}\times100 = 3.0\%$$ $$\text{Energy per Part} = \frac{1\,200\text{ kWh}}{9\,600} = 0.125\text{ kWh/part}$$

Interpretation (Economic, Environmental & Social Dimensions)

• OEE (53 %) indicates substantial room for improvement, especially in availability (breakdowns) and performance (cycle‑time variance). Targeting an OEE of ≥70 % would align with the specification’s efficiency goal.
• Cost per unit (£2.55) must be compared with the market selling price and the profit margin stipulated in the specification. If the target cost ceiling is £2.30, a cost‑reduction programme (e.g., tool‑life optimisation, energy‑saving measures) is required.
• Waste ratio (3 %) exceeds a typical target of ≤1 % for sustainable manufacturing. Investigating cutting parameters and improving material handling could reduce waste, lowering both material cost and environmental impact.
• Energy per part (0.125 kWh) contributes to the carbon footprint. Introducing energy‑efficient spindle drives or regenerative braking could improve both sustainability and operating cost.
• Quality rate (98 %) is acceptable, but the 2 % defect still generates re‑work and scrap, affecting labour morale and customer perception. A focused SPC chart on critical dimensions could help drive the quality rate above 99 %.
• Social/Health aspect: The high breakdown rate suggests possible maintenance‑team workload issues. Implementing a preventive‑maintenance schedule will improve staff safety and job satisfaction.

By addressing the identified root causes – improving preventive maintenance, refining cutting parameters, and tightening SPC control – the centre can realistically aim to raise OEE to 70 %, reduce waste to <1 %, and bring cost per unit within the target, thereby meeting both the economic and sustainability objectives of the manufacturing specification.