Operations Management: Strategies, Decision-Making, and Quality Control

Posted on Jan 9, 2025 in Naval Architecture and Marine Systems Engineering

Operations Management and Strategy

Operations refer to a function or system that transforms inputs into outputs of greater value. Operations Management (Ops Management) involves the design, operation, and implementation of productive systems. A Value Chain is a series of activities from supplier to consumer that adds value to a product.

Input → Transformation Process → Output

Evolution of Operations Management

  1. Craft Production: Handcrafting products for individual customers.
  2. Division of Labor: Dividing a job into smaller, specialized tasks.
  3. Interchangeable Parts: Standardization of parts for mass production.
  4. Scientific Management: Systematic analysis of work processes.
  5. Mass Production: High-volume production of standardized products.
  6. Quality Revolution: Focus on quality as a key competitive strategy.
  7. Lean Production: Emphasizes quality, flexibility, and efficiency.

Globalization in Operations

Reasons for Globalization:

  • Taking advantage of lower costs.
  • Accessing international markets.
  • Building reliable sources of supply.

Challenges of Globalization:

  • Quality control.
  • Reliability and security.
  • Distance within the supply chain.
  • Differing legal systems.
  • Taxes.

Strategy Formulation

  1. Primary Task: What does the firm aim to achieve?
  2. Assessing Core Competencies: What does the firm excel at compared to others?
  3. Order Qualifiers and Winners: What criteria are essential for a purchase, and what makes a product stand out?
  4. Positioning the Firm: How will the firm compete in the market?
  5. Deploying the Strategy: Implementing the chosen strategy.

Positioning the Firm:

  1. Cost
  2. Speed
  3. Quality
  4. Flexibility
  5. Innovation

Operations Decision-Making

Objective vs. Subjective Probability

  • Objective Probability: Derived from study or mathematical analysis.
  • Subjective Probability: Derived from judgment and experience.

Decision Utility

Utility is the value provided to an individual, which is difficult to quantify as it is subjective, involving positive or negative pleasure.

Subjectively Expected Utility (SEU)

SEU = Σ Pi * Ui

  • Pi: Subjective Probability
  • Ui: Utility of decision i (used in Decision Trees)

Risk: Probability of a negative outcome.

  • Risk-Seeking: Valuing uncertainty more than expected utility.
  • Risk-Averse: Valuing uncertainty less than expected utility.

Note: Utility can vary significantly between individuals.

Operations Decision-Making II

Decision Analysis is a set of quantitative decision techniques for situations where uncertainty exists.

Decision-Making Under Uncertainty

Probabilities cannot be assigned to future states.

Terminology:

  • Payoff: The outcome of a decision.
  • Payoff Table: A method for organizing and illustrating payoffs from different decisions.
  • States of Nature: Events that may occur in the future.

Decision-Making Under Risk

Probabilities can be assigned to future states (use decision trees).

Decision Criteria

  • Maximax: Choose the decision with the maximum of the maximum payoffs.
  • Maximin: Choose the decision with the maximum of the minimum payoffs.
  • Minimax Regret: For each state of nature, identify the maximum payoff and subtract each payoff from it to create a regret table. Then, choose the decision with the minimum of the maximum regrets.
  • Hurwicz: Choose the decision with the maximum payoff weighted by the coefficient of optimism, α.
  • Equal Likelihood: Choose the decision with the maximum of equally weighted outcomes.

Expected Value of Perfect Information (EVPI):

EVPI = EV with Perfect Information – EV without Perfect Information

  • EV with Perfect Information: Calculate the expected value using the maximum payoffs for each state of nature.
  • EV without Perfect Information: Use the Equal Likelihood criterion.

Decision Trees:

  • ■ = Decision Node
  • ● = State of Nature Node

Quality Management and Quality Tools

The Quality Revolution emphasizes the pursuit of defect-free products. ISO standards provide guidelines for quality products. Deming and Ishikawa advocated for integrating quality into the process rather than relying solely on inspection, leading to improved quality, reduced waste, and lower costs.

PDCA Cycle (Deming Wheel)

  1. Plan: Study the process, identify the problem, and set goals.
  2. Do: Implement the plan and measure improvements.
  3. Check: Were the goals achieved?
  4. Act: Institutionalize improvements and repeat the cycle.

Dimensions of Quality

  • Manufactured Products: Performance, features, reliability, durability, safety, conformance.
  • Services: Timeliness, courtesy, consistency, accessibility.

Employees should adhere to a code of conduct and undergo continuous training.

The Meaning of Quality

  • Customer Perspective: Quality is determined by design characteristics and price.
  • Producer Perspective: Quality is determined by conformance to production processes and cost.

These perspectives are interdependent.

Total Quality Management (TQM)

TQM encompasses training and education, customer orientation, leadership, strategic planning, employee responsibility, continuous improvement, cooperation, and statistical methods.

Pareto Analysis

Pareto Analysis identifies the frequency of different causes and their percentages:

  1. Sort causes from largest to smallest.
  2. Calculate the raw percentage and cumulative percentage for each cause.
  3. Plot the raw and cumulative percentages. The raw percentage represents the individual contribution, while the cumulative percentage sums up all preceding percentages, eventually reaching 100%. This illustrates the 80/20 rule.

Six Sigma

Six Sigma measures how much a process deviates from perfection. The goal is to implement a statistically driven process for developing and delivering virtually perfect products and services.

Process DMAIC: Define → Measure → Analyze → Improve → Control.

Cost of Quality

Quality Control:

  • Prevention Costs: Costs incurred to ensure good quality products.
  • Appraisal Costs: Costs incurred to ensure products meet customer expectations and regulatory requirements.

External failure costs are significantly higher than internal failure costs.

Product Yield: Measures the efficiency of converting inputs into outputs.

  • Yield (Y): Number of good quality items produced.
  • I: Input of items into the production process.
  • %G: Percentage of good units.
  • %R: Percentage of successfully reworked units.

Manufacturing Cost per Product: Quality cost per unit.

  • Kd: Direct manufacturing cost per unit.
  • Kr: Rework cost per unit.
  • I: Input.
  • R: Rework.
  • Y: Yield.

Quality Productivity Ratio (QPR): A productivity index that includes quality costs (refer to the textbook for details).

Statistical Process Control I

Quality Measures

  • Attribute: A product characteristic evaluated with a discrete response (e.g., Yes/No, Good/Bad).
  • Variable Measure: A product characteristic that is continuous or can be measured.

P Charts

P charts are used to establish the mean of the proportion of defective items.

  • s: Total number of samples.
  • n: Sample size.
  • di: Total defects in sample i, as a percentage.
  • z: Number of process standard deviations from -3 to 3.

Pbar = Σdi / (s * n)

di = defectives / n

C Charts

C charts are used to calculate the number of defects.

  • C bar: Sample mean number of defects.
  • z: Number of standard deviations (σs) from the process mean.

C bar = number of defects / s

σc = √C bar

X Charts

X charts are used for variable situations.

Known σ:

X bar = Σsamples / n

X 2bar = ΣXbar / k

  • k: Number of samples.
  • n: Sample size.

σx = σ / √n

Unknown σ:

R = max(n) – min(n) (for each sample)

R bar = ΣR / k

  • k: Number of samples.
  • A2: Tabular value (refer to statistical tables).

Statistical Process Control III

Process Capability

  • DCF (Design Control Factor): Measures the relationship between natural process variation and customer requirements.
  • Control Limits: Natural variations in the process.
  • Tolerances: Customer requirements.

Process Capability Ratio (Cp):

Cp = customer requirement / natural variation

  • If Cp < 1: The process is not capable (does not meet specifications).
  • If Cp = 1: The process is just capable.
  • If Cp > 1: The process is capable (within the limits).

Process Capability Index (Cpk):

  • If Cpk > 1: The process is capable of meeting design specifications.
  • If Cpk = Cp: The process is centered.

Single Sample Attribute Plan

  • N: Lot Size.
  • n: Sample Size.
  • c: Acceptance number = LPTD / AQL.
  • d: Number of defectives = items / sample.

If d ≤ c: Accept the lot.

If d > c: Reject the lot.

TERMS:

  • AQL (Acceptance Quality Level): The level of quality that the consumer desires or will accept.
  • LPTD (Lot Tolerance Percentage Defective): The limit of defective items that a consumer will accept.
  • α (Producer’s Risk): The probability of rejecting a good lot.
  • β (Consumer’s Risk): The probability of accepting a bad lot.

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