Operations Strategy and Production Systems

Introduction

Operations strategy is the pattern of decisions through which an organization configures its resources, processes, technologies, people, and supply relationships to support business objectives. In machine technology, operations strategy is especially important because product design, tooling, equipment selection, production volume, quality requirements, maintenance systems, and workforce skills are closely interconnected. A technically excellent product may fail commercially if it is too expensive to manufacture, delivered too slowly, or produced with inconsistent quality.

Production systems transform inputs—materials, labor, information, energy, and capital—into goods or services. The central managerial task is to design a system whose capabilities match the market requirements. This chapter explains how competitive priorities influence product–process design, how production systems are selected, and how capacity, technology, process mapping, product life cycle, and make-or-buy decisions are integrated.

Learning Objectives

After studying this chapter, students should be able to:

1. Explain the relationship between competitive priorities and operations strategy.
2. Relate product characteristics to process choice and manufacturing system design.
3. Distinguish job, batch, mass, and continuous production systems.
4. Apply basic capacity and utilization calculations.
5. Construct and interpret a process map.
6. Evaluate manufacturing technology choices.
7. Explain how the product life cycle affects operations decisions.
8. Analyze make-or-buy decisions using relevant cost and strategic criteria.
9. Identify professional, ethical, environmental, and technological issues in production management.

1. Operations Strategy and Competitive Priorities

Corporate strategy defines how an organization competes. Operations strategy translates that direction into decisions about facilities, processes, technology, capacity, quality systems, inventory, suppliers, and human resources. Operations strategy must be vertically aligned with business strategy and horizontally coordinated with marketing, finance, engineering, and procurement.

The principal competitive priorities are as follows:

These priorities may conflict. A highly customized product generally requires more skilled labor and flexible equipment than a standardized product, increasing cost. Very high equipment utilization can reduce unit cost but may reduce responsiveness and increase waiting time. Therefore, managers must identify qualifying priorities—minimum requirements for market participation—and order-winning priorities—attributes that secure the customer’s choice.

For example, a manufacturer of aircraft components may treat certification and quality as qualifying priorities and delivery dependability as an order winner. A producer of low-cost fasteners may compete primarily on cost and dependable delivery. A precision job shop may compete on customization, engineering support, and quality rather than price alone.

Operations capabilities and trade-offs

The traditional view of operations emphasizes trade-offs: improving one capability may weaken another. Contemporary operations management recognizes that process redesign, automation, data analytics, lean methods, and total quality management can sometimes create cumulative capabilities. Nevertheless, resources remain limited, and strategic choices are unavoidable. A firm should not promise extreme customization, very low price, immediate delivery, and perfect flexibility unless its process technology and organizational capability genuinely support all four.

2. Product–Process Design

Product design and process design should be developed together. Product design determines dimensions, tolerances, materials, number of components, assembly sequence, and inspection requirements. Process design determines how those requirements will be achieved through machines, tools, methods, labor, information, and material movement.

A design that ignores manufacturability may contain unnecessary parts, inaccessible features, excessive tolerances, or materials that are difficult to process. Design for manufacturability (DFM) seeks to reduce production difficulty and cost while preserving required performance. Design for assembly (DFA) reduces the number of parts and simplifies joining, orientation, and inspection. Design for maintenance considers access to replaceable components, diagnostic features, and safe servicing.

Important product characteristics include:

• Volume: expected quantity per period.
• Variety: number of product types and configurations.
• Product complexity: number and interdependence of parts and operations.
• Tolerance: permissible variation in a dimension or performance characteristic.
• Demand stability: predictability of quantity and timing.
• Product maturity: whether the product is new, growing, mature, or declining.

As volume increases and variety decreases, processes generally move from flexible, general-purpose arrangements toward dedicated, highly integrated flow systems. This relationship is often represented by a product–process matrix. It is not a rigid law; successful firms may deliberately combine product variety with efficient flow through modular design, postponement, flexible automation, or mass customization.

Product–process alignment

A good alignment has three characteristics:

1. Technical feasibility: equipment and methods can achieve specifications.
2. Economic feasibility: expected volume justifies process investment.
3. Strategic fit: the process supports the competitive priorities.

Misalignment creates problems. A high-volume standardized product made in a job-shop arrangement may incur excessive movement, setup, and scheduling cost. Conversely, a low-volume customized product made on a dedicated transfer line may suffer from poor utilization and costly changeovers.

3. Types of Production Systems

3.1 Job production

Job production makes a distinct product or a small number of products according to a specific customer order. Work follows a route determined by the job’s requirements. Examples include repair work, special-purpose machinery, prototypes, custom dies, and one-off fabricated structures.

Typical features are general-purpose machines, highly skilled workers, low volume, high variety, detailed job scheduling, and significant work-in-process movement. The main strengths are customization and flexibility. The weaknesses include high unit cost, long and variable lead time, complex scheduling, and difficulty achieving consistent utilization.

A job shop requires capable process planning. The planner determines operation sequence, machines, tools, fixtures, inspection points, estimated times, and material requirements. Routing sheets and computer-aided process planning systems are commonly used.

3.2 Batch production

Batch production makes a quantity of identical items before equipment is changed to produce another item. Bakeries, pharmaceutical plants, component manufacturers, and machine shops commonly use batch production.

Batch production provides a compromise between variety and efficiency. It permits shared equipment but introduces setup time, setup cost, and possible queueing. Economic batch decisions must consider demand, setup cost, holding cost, capacity, shelf life, and quality risk.

A simple economic production-size model, under restrictive assumptions, is:

where Q* is the economic order or production quantity in units, D is annual demand in units per year, S is setup or ordering cost per batch, and H is annual holding cost per unit. The formula assumes stable demand, constant costs, no shortages, known lead time, and an effectively unlimited replenishment rate in the basic order-quantity model. For internal production with finite production rate, a finite-production-rate model is more appropriate because inventory accumulates while production is running and is consumed by demand.

The quantity Q* should not be adopted mechanically. A smaller batch may be preferable when quick response, low inventory, freshness, or reduced obsolescence is strategically important.

3.3 Mass or repetitive production

Mass production makes large volumes of standardized products through a product-oriented flow. Examples include consumer appliances, automobiles, standard electrical products, and common mechanical components.

Workstations are arranged according to operation sequence. Special-purpose equipment, standardized work, line balancing, material handling systems, and preventive maintenance are important. Unit cost can be low because fixed costs are spread over many units, but the system may be inflexible and vulnerable to disruption at bottleneck stations.

A basic line-balancing relationship is:

where N_min is the theoretical minimum number of stations, t_i is the processing time of task i, Σt_i is total task time per unit, C is the allowable cycle time per station, and ⌈ ⌉ means round upward to the next whole station. This is a lower bound, not necessarily a feasible solution, because precedence constraints, equipment availability, ergonomics, and task indivisibility may require more stations.

If available production time per period is T and required output is Q, the required cycle time is:

Both T and Q must refer to the same period, and C has units of time per unit. If breaks, maintenance, and planned downtime reduce available time, they must be excluded from T.

3.4 Continuous production

Continuous production operates with uninterrupted or nearly uninterrupted flow. Oil refining, cement, chemicals, electricity generation, glass, and some food processes are examples. Materials may undergo physical or chemical transformation rather than discrete assembly.

Continuous systems usually have very high capital intensity, low product variety, high output volume, specialized control systems, and severe consequences when the process is stopped. Process control, instrumentation, safety systems, environmental monitoring, and preventive or predictive maintenance are essential.

Continuous production should not be confused with merely producing large quantities. The defining feature is the nature of the flow and the difficulty of treating individual units as separate jobs.

3.5 Comparison of production systems

Between these categories are cellular manufacturing, flexible manufacturing systems, and mass customization. A manufacturing cell groups dissimilar machines to process a family of similar parts. It can reduce movement and lead time while retaining more variety than a dedicated line.

4. Capacity Planning

Capacity is the maximum output rate that a system can achieve under specified conditions. It may be expressed in units per hour, tonnes per day, machine hours per week, or service transactions per month. Capacity is not a single permanent number: it depends on product mix, labor skills, equipment condition, operating hours, quality losses, maintenance, and scheduling rules.

Three related concepts must be distinguished:

• Design capacity: theoretical maximum under ideal conditions.
• Effective capacity: realistic maximum after planned constraints such as breaks, maintenance, setups, and product mix.
• Actual output: output achieved in a stated period.

Utilization based on design capacity is:

Efficiency relative to effective capacity is:

The denominators must be stated because utilization and efficiency are otherwise ambiguous.

Worked example: capacity and bottleneck

A machining cell has three operations. Effective weekly capacities are 480, 360, and 420 units. Actual output is 300 units. The bottleneck is the operation with the lowest effective capacity: Operation 2, at 360 units per week. Cell utilization relative to the bottleneck’s effective capacity is:

Utilization = 300/360 × 100% = 83.3%.

The unused bottleneck capacity is 60 units per week. Increasing capacity at Operations 1 or 3 will not increase total output unless Operation 2 is also improved. Possible interventions include reducing setup time, adding a parallel machine, improving yield, balancing work, or subcontracting selected operations. The bottleneck must be managed systemically; local improvement at a non-bottleneck may merely create more work-in-process.

Capacity strategy

A lead capacity strategy adds capacity before expected demand. It supports rapid delivery and growth but risks idle resources. A lag strategy adds capacity after demand is demonstrated. It reduces investment risk but may cause shortages and lost customers. A match strategy adds capacity in smaller increments as demand develops.

Long-term capacity decisions include facility location, building size, major equipment, automation, and supplier structure. Medium-term decisions include shifts, overtime, subcontracting, and workforce levels. Short-term decisions include sequencing, maintenance timing, temporary labor, and order acceptance.

5. Process Mapping and Flow Analysis

A process map is a visual representation of activities, decisions, material movement, information flow, and responsibility. It allows a team to see the complete process rather than isolated departments. Common symbols include operations, inspections, transport, delay, storage, and decisions, although organizations may use different conventions.

A useful process map should show:

1. The process start and end points.
2. Inputs, outputs, customers, and suppliers.
3. Activity sequence and decision branches.
4. Processing, transport, waiting, inspection, and storage times.
5. Responsible roles or departments.
6. Rework loops, failure points, and information delays.

Value-stream mapping adds material and information flow, inventory quantities, demand information, and time data. A process map should be validated by observing actual work. A map based only on procedures may omit informal workarounds and hidden queues.

A central lean measure is process cycle efficiency:

Value-added time is time that changes the product or service in a way the customer is willing to pay for. Total lead time includes processing, movement, inspection, waiting, and storage. The measure is diagnostic rather than an absolute performance standard. Inspection may not add customer value, but it can be necessary for risk control; eliminating it without improving the process may be irresponsible.

Process mapping supports decisions about layout, batch size, cellular manufacturing, automation, quality at source, and inventory placement. It also exposes the difference between theoretical process flow and actual performance.

6. Technology Choice in Manufacturing

Technology choice should follow requirements, not fashion. Relevant technologies include computer numerical control (CNC), robotics, programmable logic controllers, automated material handling, additive manufacturing, digital inspection, manufacturing execution systems, simulation, sensors, and industrial artificial intelligence.

Criteria for technology evaluation

A technology should be assessed using:

• capability to meet tolerance, surface finish, speed, and quality requirements;
• compatibility with product volume and variety;
• total cost of ownership, including acquisition, integration, training, maintenance, energy, software, and disposal;
• reliability, maintainability, cybersecurity, and vendor support;
• safety and ergonomic effects;
• workforce skills and organizational readiness;
• scalability and interoperability;
• environmental impact and regulatory compliance.

A simple annualized cost comparison may be used for screening:

This expression is conceptually useful, but annualized capital cost must be calculated using an appropriate depreciation or capital-recovery method. For a capital recovery factor with interest rate i and life n periods, the annual capital recovery for initial investment P and zero salvage value is:

Here A is the equivalent annual capital recovery, P is the initial investment, i is the interest rate per period, and n is the number of periods. The formula assumes a constant rate and end-of-period annual payments. If salvage value exists, it must be included separately.

Automation and digital manufacturing

Automation is most attractive when demand is sufficiently stable, tasks are repetitive or hazardous, quality requirements are strict, and the process can be standardized. Flexible automation is more suitable when product variety is significant. CNC machines and robotic systems can improve repeatability and reduce ergonomic risk, but they do not automatically eliminate poor process planning.

Artificial intelligence can support visual inspection, predictive maintenance, scheduling, demand forecasting, and anomaly detection. Its use requires representative data, validated performance, cybersecurity, human oversight, and procedures for false alarms and missed defects. An algorithm should not be allowed to override safety interlocks or regulatory controls without rigorous authorization.

7. Product Life Cycle and Operations Decisions

The product life cycle commonly includes introduction, growth, maturity, and decline. The exact pattern varies by industry, but each stage creates different operations priorities.

During introduction, a flexible job or batch process may be appropriate because design changes are frequent. During growth, processes may be standardized and moved toward cellular or repetitive production. At maturity, dedicated tooling, automation, line balancing, and supplier contracts may become economical. During decline, excess capacity and obsolete inventory become major concerns.

Product life-cycle management should include engineering change control, configuration management, spare parts, service information, and end-of-life planning. A product may be technologically mature while its manufacturing process is still unstable; managers must therefore distinguish product maturity from process maturity.

8. Make-or-Buy Decisions

A make-or-buy decision determines whether a component, service, or process should be performed internally or purchased from an external supplier. The decision is strategic as well as financial.

Relevant quantitative costs are costs that change between alternatives. Unavoidable allocated overhead should not be included merely because it appears in accounting reports. However, capacity released by outsourcing may have an alternative use, and that opportunity cost is relevant.

Worked example: relevant-cost analysis

A company requires 10,000 brackets annually. Internal production has variable cost of $7 per bracket and avoidable fixed cost of $18,000 per year. A supplier offers the brackets for $8.50 each. Allocated fixed overhead of $25,000 will continue regardless of the decision.

Internal relevant cost:

10,000 × $7 + $18,000 = $88,000.

Purchase cost:

10,000 × $8.50 = $85,000.

On purely relevant cost, buying saves $3,000 per year. The $25,000 unavoidable overhead is excluded. However, the recommendation must also consider supplier quality, delivery reliability, intellectual property, capacity availability, switching cost, dependence, labor implications, cybersecurity, and the strategic importance of the bracket. If internal capacity can produce another item contributing more than $3,000 in annual contribution, buying becomes more attractive. If the supplier is unreliable or the bracket contains proprietary technology, making may remain preferable.

A sound make-or-buy process includes:

1. Define specifications and demand.
2. Identify avoidable and unavoidable costs.
3. Include opportunity costs and transition costs.
4. Evaluate supplier capability and total risk.
5. Assess strategic knowledge, intellectual property, and resilience.
6. Establish contracts, quality agreements, audits, and performance measures.
7. Reassess the decision as demand and technology change.

Outsourcing does not eliminate responsibility. The buying firm remains accountable for product safety, regulatory compliance, ethical sourcing, and customer satisfaction.

9. Integrated Case: Redesigning a Precision-Parts Operation

Background

The following is an illustrative case. Apex Precision Components produces custom shafts and small gear assemblies for industrial equipment. It operates six general-purpose machining centers and serves approximately 40 active product configurations. Demand has increased, but customers report late deliveries and inconsistent lead times.

Problem

Management initially proposed purchasing a high-speed dedicated line. However, demand varies considerably by product, and several designs are still changing. The proposed line would have high capital cost and would be difficult to use for low-volume products.

Analysis

A process-mapping team observed the operation for two weeks. The map showed that actual machining time represented only a small portion of total lead time. Jobs waited in queues between inspection, tool preparation, and machining. Batch sizes were large because operators wished to avoid setups. The most heavily loaded machine group was the bottleneck. Quality problems were concentrated after a particular turning operation, causing rework and additional queueing.

The team classified the operation as a high-variety, medium-volume batch/job hybrid rather than a mass-production environment. The competitive priorities were dependable delivery and quality, with cost improvement as a supporting objective. A dedicated line would optimize volume efficiency but would not fit product variety or demand uncertainty.

Approach and solution

Apex adopted a phased solution:

• grouped similar parts into manufacturing families;
• created a cellular layout for the highest-volume families;
• reduced setup time through external preparation of tools and fixtures;
• introduced standardized work and first-piece approval;
• used a finite-capacity schedule at the bottleneck;
• reduced batch sizes after setup reduction;
• installed in-process measurement for the problem turning operation;
• used machine data to identify abnormal vibration and schedule maintenance;
• retained flexible machining capacity for prototypes and low-volume jobs.

A supplier was also qualified for overflow work, but not for proprietary gear designs. Supplier quality agreements specified tolerance capability, traceability, delivery performance, and corrective-action procedures.

Outcome

After implementation, average queue time declined, delivery dependability improved, and rework decreased. The firm postponed purchase of the dedicated line until demand evidence justified it. The outcome illustrates that process improvement and product–process alignment can be more appropriate than immediate automation.

Learning points

1. The bottleneck, not the most visible machine, determines system output.
2. Product variety must be considered before selecting dedicated technology.
3. Setup reduction can make smaller batches economically feasible.
4. Quality should be built into the process rather than added only through final inspection.
5. Make-or-buy decisions require strategic and risk analysis in addition to cost comparison.

10. Challenges, Ethics, and Governance

Production managers must balance productivity with worker safety, fairness, environmental responsibility, and legal compliance. Pressure to meet output targets must never justify bypassing guards, suppressing defect information, falsifying records, or exposing workers to unreasonable risk.

Important governance issues include:

• compliance with occupational safety, environmental, labor, and product regulations;
• traceability of materials and process records;
• responsible management of hazardous substances and waste;
• fair treatment of workers affected by automation or outsourcing;
• protection of employee and supplier data;
• cybersecurity of connected machines and industrial control systems;
• validation and human accountability for AI-supported decisions;
• prevention of forced labor, discrimination, and unsafe supplier practices.

Sustainability includes more than energy efficiency. Managers should consider material selection, repairability, remanufacture, product life, water use, emissions, packaging, and end-of-life recovery. Life-cycle thinking can reveal that a process with low factory cost creates greater environmental impact during use or disposal.

11. Best-Practice Guidelines

Effective operations strategy is supported by the following practices:

1. Translate customer requirements into measurable operational priorities.
2. Involve design, production, quality, maintenance, procurement, and customers early.
3. Match process type to volume, variety, complexity, and demand stability.
4. Identify bottlenecks using actual capacity and flow data.
5. Map current processes before designing future-state improvements.
6. Reduce setup, waiting, movement, defects, and unnecessary approvals.
7. Select technology through total-cost, capability, risk, and life-cycle analysis.
8. Use preventive and predictive maintenance to protect capacity.
9. Treat suppliers as part of the production system while retaining governance responsibility.
10. Review make-or-buy and capacity decisions as market conditions change.
11. Build safety, sustainability, cybersecurity, and ethics into the operating system.
12. Develop workers’ technical and analytical skills alongside automation.

Chapter Summary

Operations strategy connects business objectives with decisions about products, processes, capacity, technology, facilities, people, and suppliers. Competitive priorities include cost, quality, speed, dependability, flexibility, innovation, and sustainability. Product–process design requires alignment among volume, variety, complexity, demand, and manufacturing capability.

Job production provides maximum customization but usually has high cost and variable lead time. Batch production balances variety and efficiency but creates setup and inventory issues. Mass production supports high-volume standardized output, while continuous production is designed for uninterrupted flow and highly specialized transformation. Capacity planning distinguishes design capacity, effective capacity, and actual output; the bottleneck limits system performance.

Process mapping reveals activities, decisions, waiting, movement, information flow, and rework. Technology should be selected according to technical capability, total cost, flexibility, safety, reliability, workforce readiness, and strategic fit. Product life-cycle stages influence the appropriate balance between flexibility, capacity expansion, standardization, cost reduction, and exit planning.

Make-or-buy analysis must use relevant costs and include opportunity costs, supplier risks, intellectual property, resilience, ethics, and regulatory responsibility. Ultimately, effective production systems are not defined by equipment alone. They are integrated socio-technical systems in which people, technology, methods, information, and governance work together.

Key Terms

Operations strategy: A coordinated pattern of decisions that develops operations capabilities to support organizational strategy.

Competitive priority: An operational attribute, such as cost or quality, on which a firm competes.

Order winner: A characteristic that causes a customer to select one supplier over another.

Qualifying priority: A minimum capability required to compete in a market.

Design for manufacturability: Designing products so they can be produced efficiently and consistently.

Job production: Low-volume production of customized products, often to individual specifications.

Batch production: Production of a quantity of one product before equipment is changed for another.

Mass production: High-volume production of standardized products through an organized flow.

Continuous production: Production involving uninterrupted or nearly uninterrupted material flow.

Capacity: Maximum achievable output under stated conditions.

Bottleneck: A resource whose capacity restricts the output of the entire system.

Utilization: Actual output expressed as a percentage of design capacity.

Process map: A visual representation of process activities, decisions, flows, and delays.

Value-added time: Time that changes an output in a way valued by the customer.

Manufacturing cell: A group of equipment arranged to process a family of similar products.

Flexible automation: Automation capable of producing different products with limited changeover.

Product life cycle: The stages through which a product commonly passes from introduction to decline.

Make-or-buy decision: A decision to produce internally or obtain an item or service externally.

Relevant cost: A future cost that differs between decision alternatives.

Total cost of ownership: All acquisition, operation, maintenance, support, risk, and disposal costs associated with an asset or technology.

Review Questions

Short Answer Questions

1. Distinguish between an order-winning priority and a qualifying priority.
2. State two advantages and two limitations of batch production.
3. What is the difference between design capacity and effective capacity?
4. Why is a bottleneck important in capacity planning?
5. Identify three factors that should be considered in a make-or-buy decision besides purchase price.

Long Answer Questions

1. Explain how product volume and variety influence the choice of production system.
2. Discuss the relationship between product design, process design, and design for manufacturability.
3. Compare job, batch, mass, and continuous production with respect to equipment, labor, flexibility, and cost.
4. Explain how product life-cycle stages affect capacity, technology, quality, and inventory decisions.
5. Discuss the benefits and risks of automation and artificial intelligence in manufacturing operations.

Analytical / Application Questions

1. A factory has design capacity of 1,200 units per week, effective capacity of 1,000 units, and actual output of 850 units. Calculate utilization and efficiency, and interpret both results.
2. A company can make a component for a variable cost of $12 per unit plus $20,000 of avoidable annual fixed cost. An external supplier charges $14 per unit for 5,000 units. Which option has the lower relevant cost? Identify one strategic factor that could change the recommendation.
3. A customized machine builder is considering replacing its job-shop arrangement with a dedicated production line. Analyze whether this is appropriate, using volume, variety, demand stability, competitive priorities, and product life-cycle stage as criteria.

Multiple Choice Questions with Answers

Question 1

Which production system is most appropriate for a one-of-a-kind special-purpose machine?

A. Continuous production

B. Mass production

C. Job production

D. Repetitive line production

Correct Answer: C. Job production

Question 2

Which characteristic is most strongly associated with batch production?

A. Uninterrupted chemical flow

B. Production of one item type before setup for another

C. No equipment changeover

D. Only standardized products with negligible variety

Correct Answer: B. Production of one item type before setup for another

Question 3

A system has actual output of 850 units and design capacity of 1,000 units. What is its utilization?

A. 15%

B. 85%

C. 117.6%

D. 1,850%

Correct Answer: B. 85%

Question 4

In a production system, the bottleneck is the resource that:

A. Has the highest purchase price

B. Performs the first operation

C. Limits the output of the overall system

D. Always has the largest workforce

Correct Answer: C. Limits the output of the overall system

Question 5

If total task time is 42 seconds per unit and allowable cycle time is 10 seconds, the theoretical minimum number of stations is:

A. 3

B. 4

C. 5

D. 6

Correct Answer: C. 5

Question 6

Which priority refers to the minimum capability required to compete in a market?

A. Order winner

B. Qualifying priority

C. Bottleneck priority

D. Cost driver

Correct Answer: B. Qualifying priority

Question 7

Which time is normally excluded from value-added time in a process map?

A. Time that changes the product to customer specification

B. Time spent performing the required machining operation

C. Time spent waiting in a queue

D. Time spent forming a required feature

Correct Answer: C. Time spent waiting in a queue

Question 8

A product in the introduction stage of its life cycle generally requires greater emphasis on:

A. Flexibility and learning

B. Maximum dedicated automation

C. Capacity reduction

D. End-of-life disposal only

Correct Answer: A. Flexibility and learning

Question 9

A make-or-buy analysis should normally exclude which cost when it will continue regardless of the decision?

A. Avoidable labor cost

B. Purchase price

C. Opportunity cost

D. Unavoidable allocated overhead

Correct Answer: D. Unavoidable allocated overhead

Question 10

Which factor is a valid consideration when selecting manufacturing technology?

A. Purchase price alone

B. Total cost of ownership and process capability

C. The newest available technology in every case

D. Maximum theoretical speed regardless of demand

Correct Answer: B. Total cost of ownership and process capability