Sustainable, Safe and Resilient Manufacturing

Introduction

Manufacturing creates economic value by transforming materials, energy, information and human effort into products. It also consumes natural resources, generates emissions and wastes, exposes workers to hazards, and depends on geographically distributed suppliers and infrastructure. Sustainable manufacturing therefore cannot be reduced to energy efficiency or environmental compliance. It is the coordinated design and operation of manufacturing systems that deliver required performance while reducing environmental burden, protecting people, remaining economically viable and continuing to function under disruption.

For machine-technology professionals, this perspective is strategic. Decisions about machine tools, cutting fluids, process parameters, factory layouts, automation, maintenance, materials and suppliers influence resource consumption and risk over many years. A technically efficient process may be unsustainable if it creates hazardous waste, causes ergonomic injury, depends on a fragile supplier, or shifts environmental impacts to another life-cycle stage.

This chapter develops methods for assessing energy, materials, waste, emissions, circularity, life-cycle impacts, ergonomics, occupational safety, supply-chain resilience and sustainable technology choices. It uses internationally recognized concepts associated with life-cycle assessment, environmental management, occupational health and safety, energy management, circular economy and business-continuity practice. Standards evolve and must be checked in their current editions before being used for certification or legal compliance.

Learning objectives

After studying this chapter, students should be able to:

1. Distinguish sustainability, sustainable manufacturing, circularity, safety and resilience.
2. Establish material, energy and emissions metrics for manufacturing systems.
3. Apply life-cycle thinking and interpret life-cycle assessment results.
4. Evaluate waste-prevention and circularity strategies.
5. Identify occupational hazards and assess ergonomic exposure.
6. Explain how supply-chain structure, risk and recovery capability affect resilience.
7. Compare sustainable technology choices using technical, environmental, economic and social criteria.
8. Recommend improvements supported by metrics, standards and evidence.

1. The systems perspective

A manufacturing system has several interacting layers:

• Product design: function, material selection, durability, repairability and disassembly.
• Process technology: machining, forming, joining, additive manufacturing, heat treatment and finishing.
• Production system: machines, tooling, material handling, scheduling, maintenance and quality control.
• Facility: electricity, compressed air, heating, cooling, lighting, water and waste infrastructure.
• Supply network: raw materials, components, logistics, information and external services.
• Human and institutional system: workers, management, regulation, communities and customers.

The system boundary determines what is measured. A narrow boundary might include only electricity used by a machine. A broader boundary includes extraction of raw materials, production of tooling, transport, use of the product and end-of-life treatment. Results from different boundaries must not be compared without checking their functional unit and assumptions.

The three traditional sustainability dimensions are environmental integrity, social well-being and economic viability. A fourth practical dimension is resilience: the ability to anticipate, withstand, adapt to and recover from disturbances. These dimensions can conflict. For example, a lightweight material may reduce transport energy but require a difficult recycling process. Automation may improve consistency and reduce exposure to hazards but create new risks involving isolation, programming and job redesign.

2. Measuring resource and environmental performance

2.1 Functional units and baselines

A metric is meaningful only when its reference is clear. Common functional units include:

• kWh per component;
• kg of material input per accepted product;
• kg CO₂-equivalent per functional product;
• litres of water per batch;
• kilograms of hazardous waste per production hour;
• recordable injuries per 200,000 labour hours.

The denominator should represent useful output, not merely activity. If a machine produces defective parts, energy per manufactured part can look better than energy per accepted part. A useful production baseline therefore distinguishes total output from conforming output.

2.2 Energy performance

Manufacturing energy includes direct process energy and supporting energy. Direct energy operates a spindle, furnace or laser; supporting energy supplies pumps, fans, coolant, compressed air, lighting, heating, ventilation and information systems.

The basic specific energy indicator is:

Here, SEC is specific energy consumption, E_total is total energy consumed during the measurement period, and Q_accepted is accepted production output. Units may be kWh/part, MJ/kg or kWh per functional unit. The measure assumes that the energy boundary and output definition remain consistent.

If electricity is measured in kilowatt-hours and converted to joules:

where E_J is energy in joules and E_kWh is energy in kilowatt-hours. This follows from 1 kWh = 3.6 MJ.

A machine’s energy profile often includes idle, standby, setup, processing and auxiliary states. A useful decomposition is:

where E_base is control and standby energy, E_aux is energy for coolant, hydraulics, extraction and other auxiliaries, E_process is energy directly associated with material removal or transformation, and E_material is embodied energy in consumed materials when the boundary includes upstream production. The categories must be defined so that energy is not double-counted.

Energy assessment should identify peaks as well as totals. A compressed-air leak, poorly maintained chiller or oversized motor may consume energy continuously even when production is intermittent. Submetering, machine-state logging and production-data integration support more reliable diagnosis than monthly utility bills alone.

2.3 Materials and yield

Material efficiency compares useful material in the product with material entering the process:

Y_m is material yield, m_product is the mass incorporated into conforming products, and m_input is total material input. The measure is most useful when scrap, chips, offcuts, rejected parts and returnable material are separately recorded.

For machining, a high buy-to-fly ratio indicates that substantial material is removed before the component reaches its final mass. Near-net-shape forming, optimized blank design, additive deposition and design changes can reduce this ratio, but they may introduce energy, tooling, quality or recycling penalties.

2.4 Emissions and carbon accounting

Greenhouse-gas emissions are commonly reported as carbon dioxide equivalents. For an activity with several inputs:

where A_i is the activity data for source i—for example kWh of electricity, litres of fuel or kilograms of material—and EF_i is its emission factor in kg CO₂e per unit of activity. The sum is valid only when activity data and emission factors use compatible boundaries, time periods and units.

Electricity emissions depend on the applicable grid factor or contractual accounting method. Renewable electricity procurement does not automatically eliminate all life-cycle impacts, and claims must follow relevant reporting rules. Scope classifications distinguish direct emissions, purchased-energy emissions and value-chain emissions. A factory may have low direct emissions but significant upstream emissions from aluminium, steel, electronics or logistics.

Other emissions also matter: particulate matter, volatile organic compounds, nitrogen oxides, metal aerosols, coolant mist and noise. Carbon reduction must not be pursued by increasing toxic exposure or transferring pollution to another location.

3. Life-cycle assessment and circularity

3.1 Life-cycle assessment

Life-cycle assessment (LCA) evaluates environmental inputs and outputs across defined life-cycle stages. A conventional LCA study includes:

1. goal and scope definition;
2. functional unit and system boundary;
3. life-cycle inventory;
4. impact assessment;
5. interpretation and sensitivity analysis.

The functional unit describes the service delivered. “One kilogram of product” may be inappropriate when products differ in lifetime or performance. “One thousand operating hours at a specified load” may provide a more meaningful comparison for machines.

Life-cycle inventory data include material quantities, energy, transport, emissions, water, waste and process yields. Impact assessment can address climate change, acidification, eutrophication, resource depletion, water use and human toxicity. Different impact categories may point to different choices; therefore a single score should not replace transparent category-level results.

LCA is comparative only when alternatives provide equivalent function and data quality is comparable. Results are sensitive to allocation rules, recycling assumptions, product lifetime, electricity mix, transport distance and end-of-life scenario. A responsible decision reports these assumptions and tests important uncertainties.

3.2 Circular manufacturing

A linear model follows take–make–use–dispose. Circular manufacturing seeks to retain product, component and material value through strategies such as:

• designing for durability, repair, upgrade and disassembly;
• reducing material use without reducing required performance;
• reuse and remanufacture of components;
• recycling production scrap and end-of-life materials;
• using industrial symbiosis, where one process’s by-product becomes another process’s input;
• recovering fluids, heat and tooling where technically and safely feasible.

Recycling is not automatically circular or sustainable. Collection, sorting, contamination, remelting energy and quality loss determine actual benefit. Hazardous substances can restrict recycling routes. A design that enables easy disassembly may produce greater circular value than a product made from nominally recyclable material that cannot be economically separated.

A simple recycled-content ratio is:

where m_recycled is the mass of recycled input and m_total is total material input. This metric describes input content; it does not measure product durability, recyclability or total environmental benefit.

4. Waste prevention and cleaner production

Waste hierarchy places prevention above reuse, recycling, recovery and disposal. In a machine shop, prevention may involve optimized nesting, correct tool selection, longer tool life, process capability improvement, dry or minimum-quantity lubrication where appropriate, and reduction of rework. Segregating clean metal swarf from contaminated swarf preserves recycling value.

Lean manufacturing and environmental improvement can reinforce each other by reducing waiting, defects, excess motion, inventory and overproduction. However, lean practices are not inherently sustainable. Frequent small deliveries may reduce inventory but increase transport emissions; reduced inventory may also weaken resilience. Decisions require system-level analysis.

A process mass balance is a practical starting point:

The terms must be measured over the same boundary and period. If inventory change is ignored, apparent imbalance may reflect material held in work-in-progress rather than measurement error.

5. Occupational safety and ergonomics

5.1 Hazard identification and risk assessment

A hazard is a source or situation with potential for harm. Risk combines the likelihood of occurrence with the severity of consequence. A common qualitative model is:

This is a prioritization model, not a physical law. Scales must be defined by the organization, and high-consequence low-frequency events must not be treated as unimportant merely because their probability is difficult to estimate.

Manufacturing hazards include:

• mechanical entanglement, crushing, cutting and ejection;
• electrical energy and unexpected start-up;
• hot surfaces, molten material and fire;
• stored pneumatic, hydraulic and gravitational energy;
• cutting-fluid aerosols, solvents, dust and metal fumes;
• noise, vibration and poor lighting;
• manual handling, repetitive work and awkward posture;
• robot motion, autonomous vehicles and human–machine interaction.

The hierarchy of controls gives preference to elimination, substitution, engineering controls, administrative controls and personal protective equipment, in that order. A guard or interlock is generally more reliable than relying only on training and attention. Lockout/tagout or an equivalent energy-isolation procedure is essential during maintenance where unexpected energization is possible.

5.2 Ergonomic assessment

Ergonomics aims to fit work to human capabilities. Assessment considers force, posture, repetition, duration, vibration, reach, visual demand, recovery time and individual variation. Tools such as the Revised NIOSH lifting equation, RULA, REBA and OCRA can support screening, but they have defined scopes and should not be treated as universal injury predictors.

For a lifting task, the NIOSH approach uses a recommended weight limit based on task multipliers. In simplified form:

where RWL is recommended weight limit, LC is the load constant, and the remaining dimensionless multipliers represent horizontal location, vertical location, travel distance, asymmetry, frequency/duration and coupling. The equation applies to defined two-handed lifting conditions; it is not a general equation for pushing, pulling, carrying or highly variable tasks. The lifting index is:

A value above 1 indicates that redesign should be considered, not that injury is certain. Redesign may include reducing load, changing storage height, using a lift assist, shortening reach, reducing frequency or improving work organization.

Safety performance should include leading indicators—hazard reports closed, safety observations, preventive-maintenance completion and training quality—as well as lagging indicators such as injury rates. A low injury count in a small workforce does not prove that risk is controlled.

6. Resilient manufacturing and supply chains

Resilience is broader than redundancy. It includes anticipation, absorption, adaptation, recovery and learning. Disruptions may arise from supplier failure, cyberattack, machine breakdown, energy interruption, flood, fire, pandemic, geopolitical conflict, transport blockage or sudden demand change.

A supply-chain risk assessment maps tiers, locations, materials, lead times, capacity constraints, single-source dependencies and substitution possibilities. Important distinctions include:

• Robustness: continuing operation under disturbance;
• Redundancy: maintaining alternative capacity or suppliers;
• Agility: changing volume or mix rapidly;
• Visibility: knowing status and dependencies;
• Recoverability: restoring performance after failure.

A simple expected-loss model is:

where p_j is the probability of disruption scenario j and c_j is its consequence, such as financial loss, lost production or safety impact. This model is useful for screening but may be inadequate for correlated events, uncertain probabilities and catastrophic consequences.

A more operational measure is recovery time objective (RTO), the maximum tolerable time before a process or service must be restored, and recovery point objective (RPO), the maximum tolerable data loss measured in time. These concepts are important for production-control systems and digital manufacturing. Cybersecurity, backup testing, access control and network segmentation are therefore resilience measures, not merely information-technology concerns.

Resilience actions have trade-offs. Dual sourcing may increase cost and emissions from supplier qualification; local sourcing may reduce transport risk but not eliminate dependence on a critical raw material; inventory buffers improve continuity but tie up capital. Scenario exercises and supplier collaboration often reveal more than a one-time risk register.

7. Sustainable technology selection

Technology selection should combine multiple criteria rather than choosing the lowest purchase price. Relevant criteria include:

Life-cycle cost can be expressed as:

where C₀ is initial cost, C_t is cost in period t, r is the discount rate, S_n is residual value at the end of period n, and n is the analysis horizon. The formula assumes costs are appropriately timed and that the discount rate reflects the decision context. Energy-price escalation, inflation, taxes and uncertainty may require scenario analysis rather than a single deterministic result.

A weighted decision matrix can rank alternatives. Scores and weights must be documented, sensitivity-tested and reviewed by affected stakeholders. A high score does not prove an option is objectively sustainable; it shows how options perform under selected priorities and data.

Relevant management frameworks include ISO 14001 environmental management, ISO 50001 energy management, ISO 45001 occupational health and safety, ISO 14040 and ISO 14044 for LCA principles and requirements, ISO 14067 for product carbon footprints, and ISO 22301 for business continuity. Product and machine safety also depend on applicable national law, machinery regulations, electrical codes and sector-specific standards. Certification is evidence of a management system or conformity process, not a guarantee that every decision has minimal environmental impact.

8. Applied case: illustrative machining-cell improvement

Background

A fictional manufacturer produces precision aluminium housings in a CNC machining cell. The cell uses two machining centres, a compressor, flood coolant, cutting tools and an inspection station. Management observes rising electricity cost, high aluminium chip volume, frequent tool changes and operator discomfort during manual loading.

Problem

The factory reports total electricity but not cell-level consumption. Chips contaminated with coolant are sold at a low value. Operators repeatedly lift 18 kg boxes from floor pallets to a fixture. A single supplier provides a specialized tool insert, and delivery interruptions have previously stopped production.

Analysis

The improvement team establishes a four-week baseline using a submeter, accepted-part counts, material weighback, tool records, hazard observations and operator interviews. The functional output is one accepted housing. The team separates machine processing energy from compressor and coolant energy and records defects.

Baseline results are illustrative: 12,000 kWh are consumed to produce 4,000 accepted housings. Thus:

Material input is 9,600 kg and conforming product mass is 6,400 kg. Therefore:

The team identifies four major causes: compressor leakage, long machine idle periods, an oversized blank and unnecessary rework caused by tool wear. The risk assessment rates manual lifting and chip handling as priority hazards. Supply mapping identifies the insert as a single-source item with a six-week lead time.

Approach and solution

The team implements the following controls:

1. Repair compressed-air leaks and turn off the compressor during scheduled non-production periods.
2. Use machine-state data to schedule jobs and reduce warm idle time without compromising thermal stability.
3. Redesign the blank after confirming machining capability and material certification.
4. Establish tool-life monitoring based on wear measurements and part-quality data rather than a fixed conservative replacement interval.
5. Install a height-adjustable pallet and lift assist; redesign chip collection to reduce hand contact.
6. Segregate clean aluminium chips and use a documented coolant-drainage process.
7. Qualify a second insert supplier and hold a risk-based buffer for the critical tool.
8. Review changes through safety, quality, maintenance and operator representatives.

Outcome

After validation, electricity falls to 10,400 kWh for 4,000 accepted housings and material input falls to 8,400 kg while product mass remains 6,400 kg. The new energy indicator is:

The new material yield is:

Relative to baseline, energy per accepted housing decreases by:

The material yield increases by approximately 9.5 percentage points. The project does not claim that all improvements are caused by one intervention; production mix, weather, maintenance and measurement uncertainty are reviewed. The second supplier reduces single-source exposure, while the lift assist addresses risk at its source rather than relying only on manual-handling training.

Learning points

The case demonstrates that sustainability, safety and resilience can support one another when the team uses a common functional unit and process data. It also shows the need to prevent burden shifting: coolant segregation, quality validation, worker consultation and supplier qualification are as important as electricity reduction.

9. Governance, ethics and contemporary developments

Sustainable manufacturing requires credible claims. Organizations should define responsibilities, maintain traceable data, disclose boundaries and avoid presenting estimated reductions as measured facts. Greenwashing can occur through selective baselines, unverified offsets, vague “eco-friendly” language or reporting recycled content without considering durability and total impact.

Workers should participate in hazard identification, automation design and process change. A productivity improvement that intensifies work, removes meaningful autonomy or transfers risk to contractors is not socially sustainable. Data collected from connected machines may improve energy management but raises questions about surveillance, cybersecurity, ownership and access.

Artificial intelligence can support anomaly detection, predictive maintenance, energy forecasting, visual inspection, process optimization and supply-risk monitoring. Its use requires validated data, explainable thresholds where safety is affected, cybersecurity, human oversight and monitoring for model drift. An AI system should not be allowed to override a safety interlock merely because it predicts acceptable operation.

Contemporary developments include digital product passports, industrial energy flexibility, electrification of heat, low-carbon materials, additive and hybrid manufacturing, remanufacturing, collaborative robotics and renewable-energy integration. Each requires life-cycle and safety evaluation. Additive manufacturing may reduce material waste for complex geometries but can increase powder hazards, electricity use, post-processing and qualification requirements. Electrification can reduce local emissions while shifting environmental burdens to the electricity system and upstream equipment.

Best-practice implementation sequence

A practical improvement program follows these steps:

1. Define objectives, legal duties, stakeholders, functional units and system boundaries.
2. Establish a verified baseline for energy, material, waste, emissions, safety and supply risk.
3. Map process flows and identify hotspots, bottlenecks and burden-shifting risks.
4. Apply the hierarchy of controls and prioritize prevention over downstream treatment.
5. Generate alternatives involving design, process, equipment, organization and suppliers.
6. Evaluate alternatives using life-cycle, cost, safety, human-factor and resilience criteria.
7. Pilot changes with worker and maintenance involvement.
8. Verify performance using accepted output and consistent measurement periods.
9. Document assumptions, uncertainty, responsibilities and corrective actions.
10. Review results periodically and improve the management system.

Challenges and limitations

No single metric captures sustainability. Energy intensity can improve while absolute energy use rises because production expands. Recycling rates can increase while hazardous exposure remains unchanged. Injury rates can fall because reporting declines. Supplier diversification can increase cost and environmental burden. LCA results may be limited by poor data, uncertain future scenarios and incompatible databases. Risk matrices can create false precision, and weighted decision matrices can conceal value judgments.

Accordingly, professionals should use multiple indicators, disclose uncertainty, compare equivalent functions, consult workers and affected communities, and distinguish measured results from assumptions. Sustainable manufacturing is a process of continual learning rather than a one-time technology purchase.

Chapter Summary

Sustainable, safe and resilient manufacturing integrates environmental performance, worker protection, economic value and continuity of operation. Meaningful assessment begins with a clear functional unit, system boundary and verified baseline. Specific energy consumption, material yield, greenhouse-gas inventories and mass balances help identify process hotspots, but each metric has defined assumptions and cannot represent sustainability alone.

Life-cycle assessment prevents narrow decisions by examining impacts from raw-material extraction through production, use and end of life. Circular manufacturing seeks to retain product, component and material value through durability, repair, reuse, remanufacture and responsible recycling. Occupational safety requires hazard elimination and the hierarchy of controls, while ergonomics addresses force, posture, repetition, vibration and human capability. Resilience depends on visibility, alternative capacity, recovery planning, cybersecurity and learning, not merely on holding inventory.

Technology choices should be evaluated through technical, environmental, social, safety, economic and resilience criteria. Standards such as ISO 14001, ISO 50001, ISO 45001, ISO 14040/14044 and ISO 22301 provide useful frameworks, but compliance and certification do not replace engineering judgment. The strongest improvement programs combine reliable data, worker participation, life-cycle thinking, prevention, transparent governance and continual verification.

Key Terms

Sustainable manufacturing: Manufacturing that delivers required products while reducing environmental harm, protecting people and maintaining long-term viability.

Functional unit: Quantified reference used to compare products or processes providing a defined function.

System boundary: Definition of the processes, life-cycle stages and flows included in an assessment.

Specific energy consumption: Energy used per unit of accepted or functional output.

Material yield: Proportion of input material incorporated into conforming product.

Carbon dioxide equivalent: Common unit expressing the climate effect of greenhouse gases relative to carbon dioxide.

Life-cycle assessment: Systematic evaluation of environmental inputs and impacts across a product or process life cycle.

Circular manufacturing: Manufacturing that retains product, component and material value through cycles of use, repair, reuse and recovery.

Industrial symbiosis: Exchange in which one organization’s by-product or waste becomes another’s resource.

Hazard: Source or situation with potential to cause harm.

Risk: Combination of the likelihood and severity of harm.

Hierarchy of controls: Ordered preference for elimination, substitution, engineering, administrative and personal protective controls.

Ergonomics: Design of work, tools and systems to fit human capabilities and limitations.

Resilience: Ability to anticipate, withstand, adapt to and recover from disruption.

Redundancy: Availability of alternative capacity, suppliers, equipment or routes.

Recovery time objective: Maximum acceptable time for restoring a process or service.

Life-cycle cost: Present-value cost of acquiring, operating, maintaining and retiring an asset.

Greenwashing: Misleading communication that exaggerates or falsely presents environmental performance.

Leading indicator: Forward-looking measure of actions or conditions associated with future performance.

Scope 1, 2 and 3 emissions: Categories commonly used for direct emissions, purchased-energy emissions and other value-chain emissions.

Review Questions

Short Answer Questions

1. Why must a manufacturing metric specify a functional unit and system boundary?
2. Distinguish material yield from recycled content.
3. List the stages of a life-cycle assessment.
4. What is the purpose of the hierarchy of controls?
5. Explain the difference between robustness and resilience.

Long Answer Questions

1. Explain how energy, material, waste and emissions metrics can be integrated into a manufacturing improvement program.
2. Discuss the benefits and limitations of applying life-cycle assessment to compare two manufacturing technologies.
3. Explain how circular-design principles influence machining, remanufacturing and end-of-life recovery.
4. Describe a systematic approach to identifying and controlling hazards in an automated machining cell.
5. Analyze the trade-offs between efficiency, sustainability and supply-chain resilience.

Analytical / Application Questions

1. A cell consumes 18,000 kWh to produce 5,000 accepted parts. After improvement, it consumes 15,500 kWh for the same accepted output. Calculate both specific energy values and the percentage reduction. State the functional unit and one measurement assumption.
2. A factory has a single supplier for a critical electronic drive. Propose a resilience plan addressing supplier qualification, inventory, design substitution, cybersecurity and recovery testing. Explain at least two possible trade-offs.
3. Compare two proposed processes using energy use, material yield, worker exposure, life-cycle impacts and cost. Design a weighted decision matrix and explain how you would test whether the recommendation is sensitive to the selected weights.

Multiple Choice Questions with Answers

Question 1

Which denominator is most appropriate for a specific energy metric when defects are significant?

A. Total machine hours

B. Total raw material purchased

C. Accepted functional output

D. Number of operators

Correct Answer: C. Accepted functional output

Question 2

A process uses 10,000 kWh to produce 2,500 accepted parts. What is its specific energy consumption?

A. 0.25 kWh/part

B. 2.5 kWh/part

C. 4.0 kWh/part

D. 25 kWh/part

Correct Answer: C. 4.0 kWh/part

Question 3

Which life-cycle assessment stage defines the functional unit and system boundary?

A. Goal and scope definition

B. Life-cycle inventory

C. Impact assessment

D. Interpretation only

Correct Answer: A. Goal and scope definition

Question 4

Which option is highest in the hierarchy of controls?

A. Personal protective equipment

B. Administrative training

C. Engineering guarding

D. Elimination of the hazard

Correct Answer: D. Elimination of the hazard

Question 5

A material input is 800 kg and conforming product mass is 600 kg. What is the material yield?

A. 25%

B. 60%

C. 75%

D. 133%

Correct Answer: C. 75%

Question 6

Which statement best describes circular manufacturing?

A. Maximizing disposal speed

B. Retaining product, component and material value

C. Using only virgin materials

D. Measuring only factory electricity

Correct Answer: B. Retaining product, component and material value

Question 7

What does recovery time objective specify?

A. Maximum acceptable data loss

B. Maximum acceptable time to restore a process or service

C. Supplier payment period

D. Machine maintenance interval

Correct Answer: B. Maximum acceptable time to restore a process or service

Question 8

In the equation GHG = ∑(A_i × EF_i), what does EF_i represent?

A. Accepted output

B. Emission factor for source i

C. Energy-efficiency percentage

D. End-of-life mass

Correct Answer: B. Emission factor for source i

Question 9

Which is a leading safety indicator?

A. Number of injuries already recorded

B. Number of hazard reports closed on time

C. Total compensation paid

D. Lost production after an accident

Correct Answer: B. Number of hazard reports closed on time

Question 10

Why should LCA comparisons use equivalent functional units?

A. To ensure products provide comparable service

B. To eliminate all uncertainty

C. To guarantee one technology wins

D. To avoid measuring material flows

Correct Answer: A. To ensure products provide comparable service