Production and Operations Management- chapters 1-8

Introduction to Operations Management: 

Introduction to Operations Management 1 C H A P T E R

OM Defined: 

Page 2 OM Defined Operations management : The business function responsible for planning, coordinating, and controlling the resources needed to produce a company’s products and services

Simplified Organizational Chart: 

Page 3 Simplified Organizational Chart

Information Flows: 

Page 4 Information Flows

Information Flows To & From Operations: 

Page 5 Information Flows To & From Operations

The Role of OM in the Business: 

Page 6 The Role of OM in the Business

Value Added Defined: 

Page 7 Value Added Defined Inputs in $$ Transformation Process Outputs in $$$ Value Added by Process

Service - Manufacturing: 

Page 8 Service - Manufacturing Services : Intangible product No inventories High customer contact Short response time Labor intensive Manufacturing : Tangible product Can be inventoried Low customer contact Capital intensive Long response time

Service-Manufacturing Continuum: 

Page 9 Service-Manufacturing Continuum

OM Decisions: 

Page 10 OM Decisions Strategic decisions : Decisions that set the direction for the entire company. Broad in scope & long-term in nature Tactical decisions : Short-term & specific in nature Bound by the strategic decisions

Example: 

Page 11 Example

Major Historical Developments: 

Page 12 Major Historical Developments Industrial Revolution Late 1700s Scientific Management Early 1900s Human Relations Movement 1930s to 1960s Management Science Mid-1900s Computer Age 1970s Just-In-Time Systems 1980s Total Quality Management (TQM) 1980s Reengineering 1980s Flexibility 1990s Time-based Competition 1990s Supply Chain Management 1990s Global Competition 1990s Environmental Issues 1990s Electronic Commerce Late 1990s – Early 21 st Century

Industrial Revolution Late 1700s: 

Page 13 Industrial Revolution Late 1700s Replaced traditional craft methods Substituted machine power for labor Major contributions: James Watt (1764): steam engine Adam Smith (1776): division of labor Eli Whitney (1790): interchangeable parts

Scientific Management Early 1900s: 

Page 14 Scientific Management Early 1900s Separated ‘planning’ from ‘doing’ Management’s job was to discover worker’s physical limits through measurement, analysis & observation Major contributors: Fredrick Taylor: stopwatch time studies Henry Ford: moving assembly line

Human Relations Movement 1930s to 1960s: 

Page 15 Human Relations Movement 1930s to 1960s Recognition that factors other than money contribute to worker productivity Major contributions: Understanding of the Hawthorn effect : Study of Western Electric plant in Hawthorn, Illinois intended to study impact of environmental factors (light & heat) on productivity, but found workers responded to management’s attention regardless of environmental changes Job enlargement Job enrichment

Management Science Mid-1900s: 

Page 16 Management Science Mid-1900s Developed new quantitative techniques for common OM problems: Major contributions include: inventory modeling, linear programming, project management, forecasting, statistical sampling, & quality control techniques Played a large role in supporting American military operations during World War II

Computer Age 1970s: 

Page 17 Computer Age 1970s Provided the tool necessary to support the widespread use of Management Science’s quantitative techniques – the ability to process huge amounts of data quickly & relatively cheaply Major contributions include the development of Material Requirements Planning (MRP) systems for production control

Developments: 1980s Japanese Influence: 

Page 18 Developments: 1980s Japanese Influence Just-In-Time (JIT): Techniques designed to achieve high-volume production using coordinated material flows, continuous improvement, & elimination of waste Total Quality Management (TQM): Techniques designed to achieve high levels of product quality through shared responsibility & by eliminating the root causes of product defects Business Process Reengineering: ‘Clean sheet’ redesign of work processes to increase efficiency, improve quality & reduce costs

Developments: 1990s: 

Page 19 Developments: 1990s Flexibility: Offer a greater variety of product choices on a mass scale (mass customization) Time-based competition: Developing new product designs & delivering customer orders more quickly than competitors Supply Chain Management Cooperating with suppliers & customers to reduce overall costs of the supply chain & increase responsiveness to customers

Developments: 1990s: 

Page 20 Developments: 1990s Global competition: International trade agreements open new markets for expansion & lower barriers to the entry of foreign competitors (e.g.: NAFTA & GATT) Creates the need for decision-making tools for facility location, compliance with with local regulations, tailoring product offerings to local tastes, managing distribution networks, … Environmental issues: Pressure from consumers & regulators to reduce, reuse & recycle solid wastes & discharges to air & water

Electronic Commerce: 

Page 21 Electronic Commerce Internet & related technologies enable new methods of business transactions: E-tailing creates a new outlet for retail goods & services with global access and 24-7 availability Internet provides a cheap network for coordinating supply chain management information Developing influence of broadband & wireless

Operations Strategy & Competitiveness: 

Operations Strategy & Competitiveness 2 C H A P T E R

The Role of Business Strategy: 

Page 23 The Role of Business Strategy Business Strategy : The firm’s long-range plan based on an understanding of the marketplace Defines how a company intends to differentiate itself from competitors Individual employees & functional units use the strategy to align their efforts with each other to accomplish the overall game plan

Operations Strategy: 

Page 24 Operations Strategy OM Strategy : The long-range plan for the design & use of the operations function to support the overall business strategy: The location, size, & type of facilities The worker skills & talents required The technology & processes to be used How product & service quality will be controlled Operating efficiency  an operating s trategy

Developing a Business Strategy: 

Page 25 Developing a Business Strategy Mission : A statement defining what business the firm is in, who its customers are, & how its core beliefs shape its decision-making Environmental scanning : Monitoring the external environment for market opportunities & competitive threats Core competencies : Internal strengths & weaknesses of the firm (e.g.: personnel with special expertise, access to unique technology, & things the firm does better than competitors)

Putting it all Together: 

Page 26 Putting it all Together Business Strategy: Defined long-range plan for the company Environmental Scanning: Monitoring the business environment for market trends, threats, and opportunities Mission: Statement that defines What our business is; Who our clients are; and How our values define our business Core Competencies: Our unique strengths that help us win in the marketplace

Developing an Operations Strategy: 

Page 27 Developing an Operations Strategy Identify the competitive priorities required to support the business strategy: Common priorities include: Cost : low production costs enables the company to price its product below competitors Quality : higher performance or a more consistent product can support a price premium Time : faster delivery or consistent on-time delivery can support a price premium Flexibility : highly customized products or volume flexibility can support a price premium

Translate Priorities into Design: 

Page 28 Translate Priorities into Design Business Strategy Operations Strategy: Based on Competitive Priorities Design of Operations: Structure & Infrastructure

Design of Operations: 

Page 29 Design of Operations Structure: Facilities Flow of work Technology Infrastructure: Planning & control systems Work design & compensation

Competing on Low Cost: 

Page 30 Competing on Low Cost Eliminate wasted labor, materials, and facilities Emphasize efficient processes & high productivity Often limit the product range & offer little customization May invest in automation to increase productivity

Competing on Quality: 

Page 31 Competing on Quality High performance design: Superior features, high durability, & excellent customer service Product & service consistency: Error free delivery Close tolerances

Competing on Time: 

Page 32 Competing on Time Rapid delivery: How quickly an order is received after the order is placed On-time delivery: Sometimes items can arrive too quickly JIT firms try to avoid clutter of excess inventory Ability to deliver exactly when expected Not too early or too late

Competing on Flexibility: 

Page 33 Competing on Flexibility Product flexibility : Easily switch the production process from one item to another (substitution) Easily customize output to meet the specific requirements of a customer Volume flexibility : Rapidly increase or decrease the amount of product being produced to match demand

Understand Tradeoffs Example: Made-to-Order Pizza: 

Page 34 Understand Tradeoffs Example: Made-to-Order Pizza Fresh, Natural Ingredients Toppings & Crust Choice Slow to Cook Expensive Ingredients Low Volume Ovens QUALITY QUALITY & DESIGN FLEXIBILITY VOLUME FLEXIBILITY TIME COST

Distinguish Order Qualifiers from Order Winners: 

Page 35 Distinguish Order Qualifiers from Order Winners Order Qualifiers : Competitive priorities that a product must meet to even be considered for purchase Generally, represented by features shared by all competitors in a given market niche Order Winners : Competitive priorities that distinguish the firm’s offerings from competitors & ultimately win the customer’s order

Productivity: 

Page 36 Productivity

Productivity Measures: 

Page 37 Productivity Measures Partial Measures: A ratio of outputs to only one input (e.g.: labor productivity, machine utilization, energy efficiency) Multifactor Measures: A ratio of outputs to several, but not all, inputs Total Productivity Measures: The ratio of outputs to all inputs

Labor Productivity: 

Page 38 Labor Productivity Example: Assume two workers paint twenty-four tables in eight hours: Inputs: 16 hours of labor (2 workers x 8 hours) Outputs: 24 painted tables

Multifactor Productivity: 

Page 39 Multifactor Productivity Convert all inputs & outputs to $ value Example: 200 units produced sell for $12.00 each Materials cost $6.50 per unit 40 hours of labor were required at $10 an hour

Interpreting Productivity Measures: 

Page 40 Interpreting Productivity Measures Is the productivity measure of 1.41 in the previous example good or bad? Can’t tell without a reference point Compare to previous measures ( e.g.: last week) or to another benchmark

Productivity Growth Rate: 

Page 41 Productivity Growth Rate Can be used to compare a process’ productivity at a given time (P 2 ) to the same process’ productivity at an earlier time (P 1 )

Productivity Growth Rate: 

Page 42 Productivity Growth Rate Example: Last week a company produced 150 units using 200 hours of labor This week, the same company produced 180 units using 250 hours of labor

Product Design & Process Selection: 

Product Design & Process Selection 3 C H A P T E R

Product & Service Design: 

Page 44 Product & Service Design The process of deciding on the unique characteristics of a company’s product & service offerings Serves to define a company’s customer base, image, competition and future growth

Products versus Services: 

Page 45 Products versus Services Products: Tangible offerings Dimensions, materials, tolerances & performance standards Services: Intangible offerings Physical elements + sensory, esthetic, & psychological benefits

Strategic Importance: 

Page 46 Strategic Importance Products & service offerings must support the company’s business strategy by satisfying the target customers’ needs & preferences If not, the company will lose its customer base and its market position will erode

Step–by-Step: 

Page 47 Step–by-Step Idea Development: A need is identified & a product idea to satisfy it is put together Product Screening: Initial ideas are evaluated for difficulty & likelihood of success Preliminary Design & Testing Market testing & prototype development Final Design Product & service characteristics are set

Idea Development: 

Page 48 Idea Development Existing & target customers Customer surveys & focus groups Benchmarking Studying “best in class” companies from your industry or others and comparing their practices & performance to your own Reverse engineering Disassembling a competitor’s product & analyzing its design characteristics & how it was made Suppliers, employees and technical advances

Product Screening: 

Page 49 Product Screening Operations: Are production requirements consistent with existing capacity? Are the necessary labor skills & raw materials available? Marketing: How large is the market niche? What is the long-term potential for the product? Finance: What is the expected return on investment?

Preliminary Design & Testing: 

Page 50 Preliminary Design & Testing General performance characteristics are translated into technical specifications Prototypes are built & tested (maybe offered for sale on a small scale) Bugs are worked out & designs are refined

Final Design: 

Page 51 Final Design Specifications are set & then used to: Develop processing and service delivery instructions Guide equipment selection Outline jobs to be performed Negotiate contracts with suppliers and distributors

Break-Even Analysis: 

Page 52 Break-Even Analysis

Break-Even Analysis: 

Page 53 Break-Even Analysis Total cost = fixed costs + variable costs (quantity): Revenue = selling price (quantity) Break-even point is where total costs = revenue:

Example: 

Page 54 Example A firm estimates that the fixed cost of producing a line of footwear is $52,000 with a $9 variable cost for each pair produced. They want to know: If each pair sells for $25, how many pairs must they sell to break-even? If they sell 4000 pairs at $25 each, how much money will they make?

Example Solved: 

Page 55 Example Solved Break-even point: Profit = total revenue – total costs

Design for Manufacture (DFM): 

Page 56 Design for Manufacture (DFM) Guidelines: Minimize the number of parts Use common or standardized parts Use modular design Avoid the need for tools (e.g.: snap together components) Simplify operations

DFM Example: 

Page 57 DFM Example

DFM Benefits: 

Page 58 DFM Benefits Lower costs: Lower inventories (fewer, standardized components) Less labor required (simpler flows, easier tasks) Higher quality: Simple, easy-to-make products means fewer opportunities to make mistakes

Product Life Cycle: 

Page 59 Product Life Cycle

Concurrent Engineering: 

Page 60 Concurrent Engineering A design approach that uses multifunctional teams to simultaneously design the product & process Replaces a traditional ‘over-the-wall’ approach where one group does their part & then hands off the design to the next group

Sequential Design: 

Page 61 Sequential Design

Concurrent Engineering: 

Page 62 Concurrent Engineering

Concurrent Engineering Benefits: 

Page 63 Concurrent Engineering Benefits Representatives from the different groups can better consider trade-offs in cost & design choices as each decision is being made Development time is reduced due to less rework (traditionally, groups would argue with earlier decisions & try to get them changed) Emphasis is on problem-solving (not placing blame on the ‘other group’ for mistakes)

Process Selection: 

Page 64 Process Selection Intermittent operations: Capable of producing a large variety of product designs in relatively low volumes Continuous operations: Capable of producing one (or a few) standardized designs in very high volumes

Intermittent versus Continuous: 

Page 65 Intermittent versus Continuous

Intermittent Operations: 

Page 66 Intermittent Operations Pros: Very flexible Cons: Material handling & variable costs are high Work scheduling is difficult

Continuous Operations: 

Page 67 Continuous Operations Pros Highly efficient to produce large volumes (low variable costs) Cons Inflexible to design changes Susceptible to component failure High fixed costs for capital equipment

Continuum of Process Types: 

Page 68 Continuum of Process Types Projects Used for one-at-a-time products made exactly to customer specifications Batch processes: Used for small quantities (batches) with a high level of customization Line processes: Used for relatively high volumes with little customization Continuous processes: Used for very high volume standardized products (often commodities)

Continuum of Process Types: 

Page 69 Continuum of Process Types

Vertical Integration: 

Page 70 Vertical Integration How much of the supply chain is owned by a company? A supply chain is the series of linked activities from raw material extraction to the final customer (Chapter 4) Consider the direction of integration: Forward (toward customers) Backward (toward suppliers)

Make-or-Buy: 

Page 71 Make-or-Buy Outsourcing decisions should consider: Long-term strategic impact Existing capacity available Expertise required & available Quality issues Ramp up speed & delivery issues Total costs

Process Flowcharting: 

Page 72 Process Flowcharting Graphically defines the operation, step-by-step Used to help visualize the flow of work & information: Can help identify potential problem areas Format can be as simple or detailed as needed

Example: 

Page 73 Example

Process Technology: 

Page 74 Process Technology Automation Automated Material Handling: Automated guided vehicles (AGV) Automated storage & retrieval systems (AS/RS) Computer-Aided Design (CAD) software Robotics & Numerically-Controlled (NC) equipment Flexible Manufacturing Systems (FMS) Computer-Integrated Manufacturing (CIM)

Supply Chain Management: 

Supply Chain Management 4 C H A P T E R

What is a Supply Chain?: 

Page 76 What is a Supply Chain? A network of activities that deliver a finished product or service to the customer. The connected links of external suppliers, internal processes, and external distributors.

Components of a Typical Supply Chain: 

Page 77 Components of a Typical Supply Chain External Suppliers Internal Functions External Distributors INFORMATION

A Basic Supply Chain: 

Page 78 A Basic Supply Chain

Supply Chain Management: 

Page 79 Supply Chain Management Supply Chain Management entails: Coordinating the movement of goods and delivery of services. Sharing information between members of the supply chain. For example: sales, forecasts, promotional campaigns, and inventory levels.

Slide 80: 

Page 80 Supply Chain for Milk Products

External Suppliers: 

Page 81 External Suppliers External suppliers provide the necessary raw materials, services, and component parts. Purchased materials & services frequently represent 50% (or more) of the costs of goods sold. Suppliers are frequently members of several supply chains – often in different roles.

External Suppliers: 

Page 82 External Suppliers Tier one suppliers: Directly supplies materials or services to the firm that does business with the final customer Tier two suppliers: Provides materials or services to tier one suppliers Tier three suppliers: Providers materials or services to tier two suppliers

Internal Functions: 

Page 83 Internal Functions Vary by industry & firm, but might include: Processing Purchasing Production Planning & Control Quality Assurance Shipping

Logistics & Distribution: 

Page 84 Logistics & Distribution Logistics: getting the right material to the right place at the right time in the right quantity: Traffic Management: The selection, scheduling & control of carriers (e.g.: trucks & rail) for both incoming & outgoing materials & products Distribution Management: The packaging, storing & handling of products in transit to the end-user.

Information Sharing: 

Page 85 Information Sharing Supply chain partners can benefit by sharing information on sales, demand forecasts, inventory levels & marketing campaigns Inaccurate or distorted information leads to the Bullwhip Effect

Typical Information Flow: 

Page 86 Typical Information Flow

The Bullwhip Effect: 

Page 87 The Bullwhip Effect If information isn’t shared, everyone has to guess what is going on downstream. Guessing wrong leads to too much or too little inventory: If too much, firms hold off buying more until inventories fall (leading suppliers to think demand has fallen). If too little, firms demand a rush order & order more than usual to avoid being caught short in the future (leading suppliers to think demand has risen).

The Bullwhip Effect: 

Page 88 The Bullwhip Effect Farther away from the customer, the quality of information gets worse & worse as supply chain members base their guesses on the bad guesses of their partners. The result is increasingly inefficient inventory management, manufacturing, & logistics

Short-Circuit the Bullwhip: 

Page 89 Short-Circuit the Bullwhip Make information transparent: Use Electronic Data Interchange (EDI) to support Just-In-Time supplier replenishment Use bar codes & electronic scanning to capture & share point-of-sale data Eliminate wholesale price promotions & quantity discounts Allocate scarce items in proportion to past sales to avoid attempts to ‘game’ the system

Electronic Data Interchange: 

Page 90 Electronic Data Interchange The most common method of using computer-to-computer links to exchange data between supply chain partners in a standardized format. Benefits include: Quick transfer of information Reduced paperwork & administration Improved data accuracy & tracking capability

Vertical Integration: 

Page 91 Vertical Integration A measure of how much of the supply chain is controlled by the manufacturer. Backward integration: Acquiring control of raw material suppliers. Forward integration: Acquiring control of distribution channels.

Outsourcing: 

Page 92 Outsourcing Entails paying third-party suppliers to provide raw materials and services, rather than making them in-house. Outsourcing is increasing as many firms try to focus their internal operations on what they do best.

Whether to Outsource?: 

Page 93 Whether to Outsource? What volume is required? Are items of similar quality available in the marketplace? Is long-term demand for the item stable? Is the item critical to success of the firm? Does the item represent a core competency of the firm?

Breakeven Analysis : 

Page 94 Breakeven Analysis

Example: The Bagel Shop: 

Page 95 Example: The Bagel Shop Bill & Nancy plan to open a small bagel shop. The local baker has offered to sell them bagels at 40 cents each. However, they will need to invest $1,000 in bread racks to transport the bagels back & forth from the bakery to their store. Alternatively, they can bake the bagels at their store for 15 cents each if they invest $15,00 in kitchen equipment. They expect to sell 60,000 bagels each year. What should they do?

Example Solved: 

Page 96 Example Solved Interpretation: They anticipate selling 60,000 bagels (greater than the indifference point of 56,000). Therefore, make the bagels in-house.

Developing a Supply Base: 

Page 97 Developing a Supply Base How to chose between suppliers? One supplier or many per item? Whether to partner with suppliers?

Criteria for Choosing Suppliers: 

Page 98 Criteria for Choosing Suppliers Cost: Cost per unit & transaction costs Quality: Conformance to specifications On-time delivery: Speed & predictability

Arguments for One Supplier per Item: 

Page 99 Arguments for One Supplier per Item May only be one practical source for the item Patent issues, geography, or quality considerations) The supply chain is integrated to support JIT or EDI Making multiple suppliers impractical Availability of quantity discounts Supplier may be more responsive if it’s guaranteed all your business for the item Contract might bind you to using only one supplier Deliveries may be scheduled more easily

Arguments for Multiple Suppliers per Item: 

Page 100 Arguments for Multiple Suppliers per Item No single supplier may have sufficient capacity Competition may result in better pricing or service Multiple suppliers spreads the risk of supply chain interruption Eliminates purchaser’s dependence on a single source of supply Provides greater volume flexibility Government regulation may require multiple suppliers Antitrust issues Allows testing new suppliers without risking a complete disruption of material flow

Partnering with Suppliers: 

Page 101 Partnering with Suppliers Involves developing a long-term, mutually-beneficial relationship: Requires trust to share information, risk, opportunities, & investing in compatible technology Work together to reduce waste and inefficiency & develop new products Agree to share the gains

The Role of Warehouses: 

Page 102 The Role of Warehouses General Warehouses: Used for long-term storage of goods Distribution Warehouses: Transportation consolidation: Consolidate LTL into TL deliveries Product mixing & blending: Group multiple items from various suppliers Improve service: Reduced response time Allow for last-minute customization

Future Challenges: 

Page 103 Future Challenges Household Replenishment: Fulfilling consumer demand at the point of use (the home). Often called ‘the last mile’ problem. Freeze Point Delay (Postponement): Last minute customization to provide exactly what the consumer wants while maintaining very small inventories

Total Quality Management: 

Total Quality Management 5 C H A P T E R

What is TQM?: 

Page 105 What is TQM? Total Quality Management An integrated effort designed to improve quality performance at every level of the organization. Customer-defined quality The meaning of quality as defined by the customer.

Defining Quality: 

Page 106 Defining Quality Conformance to Specifications How well the product or service meets the targets and tolerances determined by its designers Fitness for Use Definition of quality that evaluates how well the product performs for its intended use. Value for Price Paid Quality defined in terms of product or service usefulness for the price paid.

Defining Quality: 

Page 107 Defining Quality Support Services Quality defined in terms of the support provided after the product or service is purchased Psychological Criteria A way of defining quality that focuses on judgmental evaluations of what constitutes product or service excellence.

Manufacturing vs. Service: 

Page 108 Manufacturing vs. Service Manufacturing produces a tangible product Quality is often defined by tangible characteristics Conformance, Performance, Reliability, Features Service produces an intangible product Quality is often defined by perceptual factors Courtesy, Friendliness, Promptness, Atmosphere, Consistency

Changing Focus of Quality Management: 

Page 109 Changing Focus of Quality Management

Overview of TQM Philosophy: 

Page 110 Overview of TQM Philosophy Focus on identifying root causes of reoccurring problems & correcting them A proactive, not reactive approach Allow customers to determine what’s important (customer-driven quality) Involve everyone in the organization

TQM Philosophy: 

Page 111 TQM Philosophy Maintain a Customer Focus: Identify and meet current customer needs Continually gather data (look for changing preferences) Continuous Improvement: Continually strive to improve Good enough, isn’t good enough Quality at the Source: Find the source of quality problems & correct them

TQM Philosophy: 

Page 112 TQM Philosophy Employee Empowerment: Empower all employees to find quality problems and correct them Focus on internal & external customer needs: External customers: People who purchase the company’s goods and services Internal customers: Other downstream employees who rely on preceding employees to do their job

TQM Philosophy: 

Page 113 TQM Philosophy Understanding Quality Tools: All employees should be trained to properly utilize quality control tools Team Approach: Quality is an organization-wide effort Quality circles: work groups acting as problem-solving teams Benchmarking Studying the business practices of other companies for purposes of comparison.

TQM Philosophy: 

Page 114 TQM Philosophy Manage Supplier Quality: Ensuring that suppliers engage in the same high quality practices Strategic partnering with key suppliers Quality of Design: Determining which features will be included in the final design of a product to meet customers’ needs & preferences Ease of Use: Ergonomics, easy to understand directions, etc.

TQM Philosophy: 

Page 115 TQM Philosophy Quality of Conformance to Design: Degree to which the product conforms to it’s design specifications (a measure of consistency & lack of variation) Post-Sale Service: Assisting with issues that arise after the purchase Warranty & repair issues, follow through on any promises to build a continuing relationship with the customer

Costs of Quality: 

Page 116 Costs of Quality

Ways to Improve Quality: 

Page 117 Ways to Improve Quality PDSA Cycle Quality Function Deployment Problem-solving tools

Plan-Do-Study-Act Cycle (PDSA): 

Page 118 Plan-Do-Study-Act Cycle (PDSA)

Plan-Do-Study-Act Cycle (PDSA): 

Page 119 Plan-Do-Study-Act Cycle (PDSA) Plan : Plan experiments to uncover the root cause of problems Do : Conduct the experiments Study : Study the data generated Act : Implement improvements or start over Repeat : Continuously improve

Quality Function Deployment: 

Page 120 Quality Function Deployment Compares customer requirements & product’s characteristics Understand how the product delivers quality to the customer

Comparing “Voices”: 

Page 121 Comparing “Voices” Voice of the Customer Voice of the Engineer Customer-based Benchmarks

QFD: 

Page 122 QFD In addition, QFD: Provides for competitive evaluation (benchmarks) Considers design trade-offs & synergies Facilitates target setting & developing product specifications

Setting Specifications: 

Page 123 Setting Specifications Trade-offs Targets Technical Benchmarks

Problem Solving Tools: 

Page 124 Problem Solving Tools Cause-and-Effect Diagrams Flow Charts Check Lists Control Charts Scatter Diagrams Pareto Charts Histograms

Cause-and-Effect Diagrams: 

Page 125 Cause-and-Effect Diagrams Also called Fishbone Diagrams Help identify potential causes of specific ‘effects’ (quality problems)

Flow Charts: 

Page 126 Flow Charts Diagrams of the steps involved in an operation or process

Checklists: 

Page 127 Checklists Simple forms used to record the appearance of common defects and the number of occurrences

Control Charts: 

Page 128 Control Charts Track whether a process is operating as expected

Scatter Diagrams: 

Page 129 Scatter Diagrams Illustrate how two variables are related to each other

Pareto Analysis: 

Page 130 Pareto Analysis Helps identify the degree of importance of different quality problems

Histograms: 

Page 131 Histograms Illustrate a frequency distribution

Quality Awards: 

Page 132 Quality Awards Malcolm Baldrige National Quality Award is given annually to companies demonstrating excellence Manufacturing Service Small Business Education Healthcare

MBNQA Criteria: 

Page 133 MBNQA Criteria

Quality Standards: 

Page 134 Quality Standards ISO 9000 Standards: Set of internationally recognized quality standards Companies are periodically audited & certified ISO 14000: Focuses on a company’s environmental responsibility QS 9000: Auto industry’s version of ISO 9000

Quality Gurus: 

Page 135 Quality Gurus W. Edwards Deming Joseph Juran Phillip Crosby

W. Edwards Deming: 

Page 136 W. Edwards Deming Focus on optimizing the system - not individual components Management is responsible for the system (source of 85% of problems) Continuous improvement (focus on prevention, not after-the-fact inspection) Understand variation (special versus common causes)

Joseph Juran: 

Page 137 Joseph Juran Quality = fitness for use Developed the quality trilogy: Quality planning (future orientation/design quality) Quality control (statistical control of variation) Quality improvement (continuous improvement) Emphasized the costs of quality: Understand the trade-offs between prevention & appraisal costs with failure costs

Phillip Crosby: 

Page 138 Phillip Crosby Quality requires leadership: Do it right the first time The goal is zero defects Argued that ‘quality is free’: The benefits far outweigh the cost of achieving zero defects

Statistical Quality Control: 

Statistical Quality Control 6 C H A P T E R

Quality Control Methods: 

Page 140 Quality Control Methods Descriptive statistics: Used to describe distributions of data Statistical process control (SPC): Used to determine whether a process is performing as expected Acceptance sampling: Used to accept or reject entire batches by only inspecting a few items

Descriptive Statistics: 

Page 141 Descriptive Statistics Mean (x-bar): The average or central tendency of a data set Standard deviation (sigma): Describes the amount of spread or observed variation in the data set Range: Another measure of spread The range measures the difference between the largest & smallest observed values in the data set

The Normal Distribution: 

Page 142 The Normal Distribution

Equations: 

Page 143 Equations Mean: Standard deviation:

Impact of Standard Deviation: 

Page 144 Impact of Standard Deviation

Skewed Distributions (One Form of Non-Normal Distribution): 

Page 145 Skewed Distributions (One Form of Non-Normal Distribution)

SPC Methods: 

Page 146 SPC Methods Control charts Use statistical limits to identify when a sample of data falls within a normal range of variation

Setting Limits Requires Balancing Risks: 

Page 147 Setting Limits Requires Balancing Risks Control limits are based on a willingness to think something’s wrong, when it’s actually not (Type I or alpha error), balanced against the sensitivity of the tool - the ability to quickly reveal a problem (failure is Type II or beta error)

Types of Data: 

Page 148 Types of Data Variable level data: Can be measured using a continuous scale Examples: length, weight, time, & temperature Attribute level data: Can only be described by discrete characteristics Example: defective & not defective

Control Charts for Variable Data: 

Page 149 Control Charts for Variable Data Mean (x-bar) charts Tracks the central tendency (the average value observed) over time Range (R) charts: Tracks the spread of the distribution over time (estimates the observed variation)

x-Bar Computations: 

Page 150 x-Bar Computations

Example: 

Page 151 Example Assume the standard deviation of the process is given as 1.13 ounces Management wants a 3-sigma chart (only 0.26% chance of alpha error) Observed values shown in the table are in ounces Time 1 Time 2 Time 3 Observation 1 15.8 16.1 16.0 Observation 2 16.0 16.0 15.9 Observation 3 15.8 15.8 15.9 Observation 4 15.9 15.9 15.8 Sample means 15.875 15.975 15.9

Computations: 

Page 152 Computations Center line (x-double bar): Control limits:

2nd Method Using R-bar: 

Page 153 2 nd Method Using R-bar

Control Chart Factors: 

Page 154 Control Chart Factors

Example: 

Page 155 Example Time 1 Time 2 Time 3 Observation 1 15.8 16.1 16.0 Observation 2 16.0 16.0 15.9 Observation 3 15.8 15.8 15.9 Observation 4 15.9 15.9 15.8 Sample means 15.875 15.975 15.9 Sample ranges 0.2 0.3 0.2

Computations: 

Page 156 Computations

Example x-bar Chart: 

Page 157 Example x-bar Chart

R-chart Computations (Use D3 & D4 Factors: Table 6-1): 

Page 158 R-chart Computations (Use D3 & D4 Factors: Table 6-1)

Example R-chart: 

Page 159 Example R-chart

Using x-bar & R-charts: 

Page 160 Using x-bar & R-charts Use together Reveal different problems

Control Charts for Attribute Data: 

Page 161 Control Charts for Attribute Data p-Charts: Track the proportion defective in a sample c-Charts: Track the average number of defects per unit of output

Process Capability: 

Page 162 Process Capability A measure of the ability of a process to meet preset design specifications: Determines whether the process can do what we are asking it to do Design specifications (a/k/a tolerance limits): Preset by design engineers to define the acceptable range of individual product characteristics (e.g.: physical dimensions, elapsed time, etc.) Based upon customer expectations & how the product works (not statistics!)

Measuring Process Capability: 

Page 163 Measuring Process Capability Compare the width of design specifications & observed process output

Capability Indexes: 

Page 164 Capability Indexes Centered Process (C p ): Any Process (C pk ):

Example: 

Page 165 Example Design specifications call for a target value of 16.0 +/-0.2 microns (USL = 16.2 & LSL = 15.8) Observed process output has a mean of 15.9 and a standard deviation of 0.1 microns

Computations: 

Page 166 Computations C p : C pk :

Three Sigma Capability: 

Page 167 Three Sigma Capability Until now, we assumed process output should be modeled as +/- 3 standard deviations By doing so, we ignore the 0.26% of output that falls outside +/- 3 sigma range The result: a 3-sigma capable process produces 2600 defects for every million units produced

Six Sigma Capability: 

Page 168 Six Sigma Capability Six sigma capability assumes the process is capable of producing output where +/- 6 standard deviations fall within the design specifications (even when the mean output drifts up to 1.5 standard deviations off target) The result: only 3.4 defects for every million produced

3-Sigma versus 6-Sigma: 

Page 169 3-Sigma versus 6-Sigma

Just-In-Time Systems: 

Just-In-Time Systems 7 C H A P T E R

Just-In-Time: 

Page 171 Just-In-Time Getting the right quantity of goods to the right place – exactly when needed! Just-In-Time= not late & not early

Philosophy of JIT: 

Page 172 Philosophy of JIT Elimination of waste Broad view of operations Simplicity Continuous improvement Visibility Flexibility

Eliminate Waste: 

Page 173 Eliminate Waste Waste is anything that doesn’t add value: Unsynchronized production Inefficient & unstreamlined layouts Unnecessary material handling Scrap & rework

Broad View of Operations: 

Page 174 Broad View of Operations Understanding that operations is part of a larger system Goal is to optimize the system – not each part: Avoid narrow view: “That’s not in my job description!” Avoid sub-optimization

Simplicity: 

Page 175 Simplicity It’s often easy to develop complex solutions to problems by adding extra steps Goal is to find a simpler way to do things right: Less chance to forget extra step Fewer opportunities to make mistakes More efficient

Continuous Improvement: 

Page 176 Continuous Improvement Traditional viewpoint: “It’s good enough” JIT viewpoint: “If it’s not perfect, make it better”

Visibility: 

Page 177 Visibility Waste can only be eliminated after it’s discovered Clutter hides waste JIT requires good housekeeping

Visibility: 

Page 178 Visibility

Flexibility: 

Page 179 Flexibility Easy to make volume changes: Ramp up & down to meet demand Easy to switch from one product to another: Build a mix of products without wasting time with long changeovers

Three Elements of JIT: 

Page 180 Three Elements of JIT

JIT Manufacturing: 

Page 181 JIT Manufacturing Kanbans & pull production systems Quick setups & small lots Uniform plant loading Flexible resources Efficient facility layouts

Pull Production & Kanbans: 

Page 182 Pull Production & Kanbans

Number of Kanbans Required: 

Page 183 Number of Kanbans Required N = number of containers D = demand rate at the withdraw station T = lead time from supply station C = container size

Quick Setups & Small Lots: 

Page 184 Quick Setups & Small Lots Setup times = time required to get ready E.g .: clean & calibrate equipment, changing tools, etc. Internal versus external setups Stop production or setup will still running Internal setups = lost production time Inefficient setups = waste

Uniform Plant Loading: 

Page 185 Uniform Plant Loading

Flexible Resources: 

Page 186 Flexible Resources General purpose equipment: E.g .: drills, lathes, printer-fax-copiers, etc. Capable of being setup to do many different things Multifunctional workers: Cross-trained to perform several different duties

Efficient Facility Layouts: 

Page 187 Efficient Facility Layouts Workstations in close physical proximity to reduce transport & movement Streamlined flow of material Often use: Cellular Manufacturing (instead of job shops) U-shaped lines: (allows material handler to quickly drop off materials & pick up finished work)

Job Shop Layout: 

Page 188 Job Shop Layout

Cellular Manufacturing: 

Page 189 Cellular Manufacturing

TQM & JIT: 

Page 190 TQM & JIT Quality at the Source Jidoka (authority to stop line) Poka-yoke (foolproof the process) Preventive maintenance

Respect for People: The Role of Workers: 

Page 191 Respect for People: The Role of Workers Cross-trained workers Actively engaged in problem-solving Workers are empowered Everyone responsible for quality Workers gather performance data Team approaches used for problem-solving Decision made bottom-up Workers responsible for preventive maintenance

Slide 192: 

Page 192 Respect for People: The Role of Management Responsible for culture of mutual trust Serve as coaches & facilitators Support culture with appropriate incentive system Responsible for developing workers Provide multi-functional training Facilitate teamwork

Supplier Relations & JIT: 

Page 193 Supplier Relations & JIT Use single-source suppliers Build long-term relationships Co-locate facilities to reduce transport Stable delivery schedules Share cost & other information

Benefits of JIT: 

Page 194 Benefits of JIT Smaller inventories Improved quality Reduced space requirements Shorter lead times Lower production costs Increased productivity Increased machine utilization Greater flexibility

Implementing JIT Manufacturing: 

Page 195 Implementing JIT Manufacturing Identify & fix problems Reorganize workplace Remove clutter & designate storage Reduce setup times Reduce lot sizes & lead times Implement layout changes Cellular manufacturing & close proximity Switch to pull production Extend methods to suppliers

JIT in Services: 

Page 196 JIT in Services Multifunctional workers Reduce cycle times Minimize setups Parallel processing Good housekeeping Simple, highly-visible flow of work

Forecasting: 

Forecasting 8 C H A P T E R

Principles of Forecasting: 

Page 198 Principles of Forecasting Forecasts are rarely perfect Grouped forecasts are more accurate than individual items Forecast accuracy is higher for shorter time horizons

Step-by-Step: 

Page 199 Step-by-Step Decide what to forecast: Level of detail, units of analysis & time horizon required Evaluate & analyze appropriate data Identify needed data & whether it’s available Select & test the forecasting model Cost, ease of use & accuracy Generate the forecast Monitor forecast accuracy over time

Types of Forecasting Methods: 

Page 200 Types of Forecasting Methods Qualitative methods: Forecasts generated subjectively by the forecaster Quantitative methods: Forecasts generated through mathematical modeling

Qualitative Methods: 

Page 201 Qualitative Methods Strengths: Incorporates inside information Particularly useful when the future is expected to be very different than the past Weaknesses: Forecaster bias can reduce the accuracy of the forecast

Types of Qualitative Models: 

Page 202 Types of Qualitative Models

Quantitative Methods: 

Page 203 Quantitative Methods Strengths: Consistent and objective Can consider a lot of data at once Weaknesses: Necessary data isn’t always available Forecast quality is dependent upon data quality

Types of Quantitative Methods: 

Page 204 Types of Quantitative Methods Time Series Models: Assumes the future will follow same patterns as the past Causal Models: Explores cause-and-effect relationships Uses leading indicators to predict the future

Patterns in Time Series Data: 

Page 205 Patterns in Time Series Data

Logic of Time Series Models: 

Page 206 Logic of Time Series Models Data = historic pattern + random variation Historic pattern may include: Level (long-term average) Trend Seasonality Cycle

Time Series Models: 

Page 207 Time Series Models Naive: The forecast is equal to the actual value observed during the last period Simple Mean: The average of all available data Moving Average: The average value over a set time period (e.g.: the last four weeks) Each new forecast drops the oldest data point & adds a new observation

Weighted Moving Average: 

Page 208 Weighted Moving Average All weights must add to 100% or 1.00 Allows the forecaster to emphasize one period over others Differs from the simple moving average that weights all periods equally

Exponential Smoothing: 

Page 209 Exponential Smoothing Forecast quality is highly dependent on selection of alpha: Low alpha values generate more stable forecasts High alpha values generate forecasts that respond quickly to recent data Issue is whether recent changes reflect random variation or real change in long-term demand

Forecasting Trends: 

Page 210 Forecasting Trends Trend-adjusted exponential smoothing Three step process: Smooth the level of the series: Smooth the trend: Calculate the forecast including trend:

Adjusting for Seasonality: 

Page 211 Adjusting for Seasonality Calculate the average demand per season E.g.: average quarterly demand Calculate a seasonal index for each season of each year: Divide the actual demand of each season by the average demand per season for that year Average the indexes by season E.g .: take the average of all Spring indexes, then of all Summer indexes, ...

Adjusting for Seasonality: 

Page 212 Adjusting for Seasonality Forecast demand for the next year & divide by the number of seasons Use regular forecasting method & divide by four for average quarterly demand Multiply next year’s average seasonal demand by each average seasonal index Result is a forecast of demand for each season of next year

Casual Models : 

Page 213 Casual Models Often, leading indicators hint can help predict changes in demand Causal models build on these cause-and-effect relationships A common tool of causal modeling is linear regression:

Linear Regression: 

Page 214 Linear Regression

Forecast Accuracy: 

Page 215 Forecast Accuracy Forecasts are rarely perfect Need to know how much we should rely on our chosen forecasting method Measuring forecast error : Note that over-forecasts = negative errors and under-forecasts = positive errors

Tracking Forecast Error Over Time: 

Page 216 Tracking Forecast Error Over Time Mean Absolute Deviation (MAD): A good measure of the actual error in a forecast Mean Square Error (MSE): Penalizes extreme errors Tracking Signal Exposes bias (positive or negative)

Factors for Selecting a Forecasting Model: 

Page 217 Factors for Selecting a Forecasting Model The amount & type of available data Degree of accuracy required Length of forecast horizon Presence of data patterns