Operations Management — Module 2: Tools and Techniques for Global Operations Management
Course Code: BBA5B08 • Comprehensive DegreeLive Lecture Notes
6. Statistical Process Control for Quality Management: Control Charts
Statistical Process Control (SPC)
Statistical Process Control (SPC) is a quality management technique that uses statistical methods to monitor, control, and improve production processes. The main objective of SPC is to identify variations in a process before they result in defective products. Instead of inspecting quality only after production, SPC continuously monitors the process during production.
Objectives of SPC:
- Maintain consistent quality
- Detect process variations
- Reduce defects and waste
- Improve productivity
- Support continuous improvement
Example: A bottling company regularly checks the amount of liquid filled in bottles to ensure consistency.
Control Charts
A control chart is a graphical tool used to monitor process performance over time. It helps determine whether a process is operating within acceptable limits or whether corrective action is required.
Interpretation: Points within control limits indicate the process is under control. Points outside control limits indicate possible problems requiring investigation.
Benefits of Control Charts
- Early detection of quality problems
- Reduction of defects
- Improved process stability
- Better decision-making
Example: A factory producing screws may use control charts to monitor screw length and detect unusual variations before batches become defective.
7. Process and Capacity Design in Global Operations: Bottlenecks, Capacity Constraints and Operational Hedging Strategies
Process Design
Refers to planning how goods and services will be produced. It determines the sequence of activities, technologies, resources, and workflows needed to create value.
Objectives:
- Improve productivity & reduce waste
- Ensure quality
- Lower operational costs
- Increase customer satisfaction
Example: Automobile assembly lines designed for smooth production flow.
Capacity Design
Involves determining the maximum output that a system can produce within a given period. Organizations must balance capacity with customer demand.
Importance:
- Avoids underutilization
- Prevents overloading
- Improves efficiency
- Supports customer service
Example: A manufacturing plant planning how many units it can produce daily.
Bottlenecks & Capacity Constraints
Bottlenecks: A stage in the process where the flow of work is restricted due to limited capacity. Bottlenecks slow down the entire production system.
Example: If packaging takes longer than manufacturing, packaging becomes the bottleneck.
Capacity Constraints: Limitations that prevent an organization from meeting desired output levels (e.g., Limited machinery, insufficient workforce, raw material shortages, financial limitations, storage limitations).
Operational Hedging Strategies
Operational hedging refers to strategies used to reduce risks arising from uncertainties in global operations. Companies spread operations across different locations to reduce the impact of disruptions.
- Reduces supply chain risk
- Improves flexibility
- Enhances business continuity
- Reduces dependence on one location
Example: A multinational company manufacturing products in multiple countries instead of relying on a single factory.
8. Forecasting Techniques for Global Operations: Qualitative and Quantitative, Error in Forecasting Methods
Forecasting is the process of predicting future events, demand, sales, or operational requirements based on available information. Accurate forecasting helps organizations plan production, inventory, staffing, and investments.
Qualitative Forecasting
Relies on expert opinions, experience, judgment, and market insights. Useful when historical data is limited (e.g., predicting demand for a completely new product).
Methods:
- Expert Opinion: Forecasts based on specialist knowledge.
- Delphi Method: Experts provide forecasts independently until consensus is reached.
- Market Research: Customer surveys and market studies.
Quantitative Forecasting
Uses historical data and mathematical techniques. Suitable when reliable data is available (e.g., using previous years' sales data to estimate future demand).
Methods:
- Time Series Analysis: Uses past trends to predict future values.
- Moving Average: Calculates averages over specific periods.
- Regression Analysis: Examines relationships between variables.
Difference Between Qualitative and Quantitative Forecasting
| Qualitative Forecasting | Quantitative Forecasting |
|---|---|
| Based on judgment | Based on data |
| Useful for new products | Useful when historical data exists |
| Subjective | Objective |
| Less mathematical | More mathematical |
Error in Forecasting Methods
Forecasts are rarely perfect and may contain errors.
9. Global Inventory Management and Control: ABC and EOQ
Inventory Management involves planning, storing, controlling, and monitoring inventory to ensure the right products are available at the right time. In global business, inventory management becomes more complex due to international suppliers, transportation delays, and varying market demand.
ABC Analysis
ABC Analysis is a technique used to classify inventory based on importance and value:
| Category | Characteristics & Management Control |
|---|---|
| Category A | High value, low quantity. Requires strict, continuous control (e.g., Smartphone processors). |
| Category B | Medium value, medium quantity. Requires normal control. |
| Category C | Low value, high quantity. Requires less control (e.g., Packaging materials). |
EOQ (Economic Order Quantity)
EOQ is a technique used to determine the optimal order quantity that minimizes total inventory costs. The goal is to balance Ordering costs and Inventory carrying costs.
- Reduces inventory costs
- Avoids overstocking
- Improves inventory planning
- Optimizes purchasing decisions
Example: A company calculates the ideal quantity of raw materials to order each time to minimize overall costs.
10. Just-in-Time and Lean Systems Strategies for Global Operations
Just-in-Time (JIT)
Just-in-Time is an inventory management philosophy where materials and products arrive exactly when needed for production. The objective is to minimize inventory levels and eliminate waste.
Advantages of JIT
- Lower inventory costs
- Reduced storage requirements
- Faster production flow
- Improved quality
Limitations of JIT
- Highly dependent on suppliers
- Vulnerable to supply chain disruptions
- Requires accurate demand forecasting
Example: An automobile manufacturer receiving components shortly before assembly.
Lean Systems
Lean systems focus on maximizing customer value while minimizing waste. Lean management seeks to improve efficiency throughout the entire operation.
8 Types of Waste Identified in Lean Systems:
1. Overproduction
Producing more than required.
2. Waiting
Idle time between activities.
3. Transportation
Unnecessary movement of materials.
4. Excess Inventory
Holding more inventory than needed.
5. Defects
Producing faulty products.
6. Unnecessary Motion
Inefficient worker movement.
7. Overprocessing
Performing unnecessary work.
8. Underutilized Talent
Failure to use employee skills.
Lean Principles:
- Identify Customer Value: Understand what customers truly value.
- Map the Value Stream: Identify activities that create value.
- Create Continuous Flow: Ensure smooth movement of work.
- Establish Pull System: Produce according to customer demand.
- Pursue Perfection: Continuously improve processes.
Difference Between JIT and Lean Systems
| Just-in-Time (JIT) | Lean Systems |
|---|---|
| Focuses mainly on inventory reduction | Focuses on eliminating all forms of waste |
| Ensures materials arrive when needed | Improves the entire process |
| Inventory management approach | Overall management philosophy |
| Narrower scope | Broader scope |
Example: Toyota successfully uses both JIT and Lean principles to achieve high efficiency, low costs, and superior product quality.
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