Production Planning and Control (ME-802 (D)) - Unit 5 Short Notes

UNIT 5: PRODUCTION PLANNING AND CONTROL

I. FUNDAMENTALS OF PRODUCTION SYSTEMS

Job Production vs. Batch Production

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Exam Focus: Be ready to compare both in a table format. Job = "one-off", Batch = "group of same items". Applications are key differentiators.

Role of PPC in National Development (India Context)

Production Planning and Control (PPC) is crucial for developing economies like India to:

• Improve Industrial Efficiency: Reduces waste (time, material, idle capacity), optimizes resource use.

• Boost Economic Growth: Ensures timely availability of goods, supports infrastructure projects, increases exports.

• Employment Generation: Efficient planning creates stable, productive jobs.

• Technology Adoption: Facilitates implementation of modern systems (MRP, ERP) in SMEs.

• Quality & Standards: Enforces consistent quality, helping meet global standards (e.g., Make in India).

• Resource Optimization: Manages scarce capital and raw materials effectively.

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Common Pitfall: Don't just list points. Link each to India's context—e.g., "Reducing waste helps combat India's high logistics costs (~13-14% of GDP)."

II. FORECASTING TECHNIQUES

Sales Forecasting

Definition: Estimating future sales volume/value for a given period under a proposed marketing plan.

Objectives:

• Determine production volume & capacity needs.

• Set inventory & purchasing policies.

• Plan financial requirements (cash flow).

• Establish sales targets & quotas.

Fields of Application in Production Planning:

1. Master Production Schedule (MPS) Input: Drives what to produce and when.

2. Capacity Planning: Determines if current capacity meets forecasted demand.

3. Material Requirements Planning (MRP): Triggers component ordering.

4. Workforce Planning: Hiring, training, or layoff decisions.

5. Budgeting: Production, inventory, and sales budgets.

Market Analysis

Role in Forecasting & Planning: Provides data foundation for sales forecasts. Analyzes market size, trends, competition, customer behavior to predict demand.

Methods & Data Sources:

• Surveys: Customer/dealer interviews (primary data).

• Trend Analysis: Historical sales data extrapolation (time series).

• Market Testing: Pilot launches in limited areas.

• Competitor Analysis: Studying rivals' sales, market share.

• Economic Indicators: GDP growth, disposable income, industry reports (secondary data).

• Delphi Method: Expert consensus for long-term forecasts.

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Exam Ready: "Market analysis feeds into sales forecasting by providing external data (customer trends, competition) while forecasting uses internal data (past sales)."

III. METHOD STUDY AND WORK MEASUREMENT

Method Study vs. Work Measurement

Procedure of Method Study (Steps):

1. Select the job/process to study.

2. Record all facts (use charts: process, flow, activity).

3. Examine critically (question purpose, sequence, location, etc.).

4. Develop new, improved method (eliminate, combine, rearrange, simplify).

5. Install the new method (train, change layouts).

6. Maintain by regular checks.

Principles of Motion Economy

Fundamental principles to reduce fatigue & time by optimizing motions:

1. Use Symmetrical motions (both hands start/end together).

2. Use continuous, curved motions (avoid sharp direction changes).

3. Use lowest possible motion classification (class 1 = finger, class 2 = finger+wrist, etc.).

4. Use momentum (assist with machine or body weight).

5. Minimize muscle effort (use proper tool design, jigs).

6. Place tools/materials in fixed, optimal locations (minimize search/reach).

7. Design workplace for good posture (avoid bending, twisting).

Relation to Workplace Layout: These principles directly dictate layout—tools within "normal working area" (from left to right, within easy reach), materials prepositioned, work surface height appropriate.

Predetermined Motion Time Systems (PMTS)

Pre-built database of times for basic motions (e.g., reach, grasp, move, release).

In Man-Machine Systems: PMTS times human motions only; machine cycle times are added separately. Useful for balancing manual work with automated stations.

Synthesis from Standard Data

Concept: Building standard times for complex jobs by adding times from a database of standard elemental times (for similar tasks, tools, materials).

Procedure:

1. Break job into elements (e.g., "drill 10mm hole in mild steel").

2. For each element, find matching standard data entry (adjust for variables like material, tool size, diameter).

3. Sum elemental times + allowances (personal, fatigue, delay) = Standard Time.

4. Validate with occasional stopwatch studies.

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Exam Trap: "Synthesis" ≠ "PMTS". PMTS times motions; synthesis uses pre-determined elemental times (which may come from PMTS or past studies).

IV. PRODUCTION PLANNING

Information Requirements for Effective Planning

Essential data inputs:

1. Demand Forecast: What, how much, when?

2. Current Inventory: Raw material, WIP, finished goods levels.

3. Production Capacity: Machine hours, labor hours, shifts available.

4. Lead Times: Procurement, processing, delivery times.

5. Bill of Materials (BOM): Component hierarchy & quantities.

6. Routing: Sequence of operations, work centers.

7. Supplier Reliability: Delivery performance, quality.

8. Workforce Skills & Availability.

9. Maintenance Schedules: Machine downtime planned.

10. Financial Constraints: Budget for materials, overtime.

Master Production Schedule (MPS)

Definition: A time-phased plan stating what finished goods are to be produced, in what quantities, and when (typically weekly).

Purpose:

• Translates overall business plan into specific production targets.

• Drives MRP (inputs: MPS, BOM, inventory).

• Communicates to sales, production, purchasing.

Development Process & Inputs:

1. Inputs:

   • Sales forecast & actual orders.

   • Current inventory & projected on-hand.

   • Production capacity (available-to-promise).

   • Business policies (e.g., minimum order quantities).

2. Process:

   • Net requirements = Gross requirements - On-hand - Scheduled receipts.

   • Time-phasing: Apply lead time to determine planned order releases.

   • Resolve capacity conflicts (crashing, overtime, subcontracting).

3. Output: MPS table (Item, Period 1,2,3...; columns: Forecast, Customer Orders, Projected On-Hand, MPS, Available-to-Promise).

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Key Formula: Projected On-Hand = Previous On-Hand + Scheduled Receipts + MPS - Forecast - Customer Orders.

V. SCHEDULING AND LINE BALANCING

Scheduling Situations and Methodologies

Types of Scheduling Problems:

• Job Shop: Custom orders, functional layout, high variety, low volume. (e.g., tool room).

• Flow Shop: Products follow same sequence, line/group layout, high volume. (e.g., assembly line).

• Project: Unique, one-time, complex (e.g., construction).

Methodology Explained: Johnson’s Rule (for 2-machine Flow Shop to minimize makespan)

• Rule: For each job, find shortest processing time among all unscheduled jobs.

  • If shortest is on Machine 1, schedule job first.

  • If shortest is on Machine 2, schedule job last.

  • Repeat until all scheduled.

• Objective: Minimize total time to complete all jobs (makespan).

• Assumptions: All jobs available at time zero, no preemption.

Example: Jobs A, B, C with times (M1, M2): A(3,5), B(2,4), C(5,1).

• Shortest overall = 2 (B on M1) → Schedule B first.

• Next shortest = 1 (C on M2) → Schedule C last.

• Remaining A in middle. Sequence: B → A → C.

Line Balancing Using Heuristic Methods

Goal: Assign tasks to workstations so that:

• All tasks are assigned.

• Precedence relations are respected.

• Cycle time ≤ desired cycle time.

• Number of stations minimized (or efficiency maximized).

Heuristic Methods (Rules):

1. Ranked Positional Weight (RPW):

   • Positional weight = task time + sum of times of all successor tasks.

   • Rank tasks by descending weight.

   • Assign highest-ranked task to first station with available time, respecting precedence.

2. Largest Candidate Rule (LCR):

   • Select task with largest time that fits in current station and whose predecessors are already assigned.

3. Number of Followers: Choose task with most immediate successors.

Steps for RPW:

1. List tasks, times, predecessors.

2. Compute positional weight for each task.

3. Sort tasks descending by weight.

4. Starting from station 1, fill with highest-ranked task that fits & predecessors are assigned.

5. Repeat for next station.

Transportation Problem

Formulation: Minimize total transportation cost from multiple sources (plants) to multiple destinations (warehouses) with supply & demand constraints.

Given Problem (May 2024):

• Sources (Plants): A(800), B(500), C(900) → Total Supply = 2200.

• Destinations (Warehouses): D(400), E(400), F(500), G(400), H(800) → Total Demand = 2500.

• Cost Matrix (Rs./unit):

Solution via Least Cost Method (LCM):

1. Allocate to cell with lowest cost (min of all = 3, A→H).

   • Allocate min(supply_A, demand_H) = min(800,800)=800 to A-H.

   • Update: A supply=0, H demand=0.

2. Next lowest cost = 4 (B→D and C→E and C→H). Choose any, say B→D (4).

   • Allocate min(500,400)=400 to B-D.

   • Update: B supply=100, D demand=0.

3. Next lowest = 4 (C→E and C→H). C→E (4).

   • Allocate min(900,400)=400 to C-E.

   • Update: C supply=500, E demand=0.

4. Next lowest = 4 (C→H) but H demand=0. Next = 5 (A→D) but A supply=0. Next = 6 (A→F, A→G, B→G, C→F, C→G). Choose A→F (6).

   • Allocate min(0,500)=0 (A exhausted). Skip.

   • Next A→G (6) → 0.

   • Next B→G (6): B supply=100, G demand=400 → allocate 100 to B-G.

   • Update: B supply=0, G demand=300.

5. Remaining: C supply=500, destinations F(500), G(300), H(0). Costs: C→F=6, C→G=6.

   • Allocate to C-F: min(500,500)=500 → C-F=500.

   • Update: C supply=0, F demand=0.

6. Last: C supply=0, G demand=300 → but C exhausted. Check: Total allocated = 800+400+400+100+500 = 2200. Supply exhausted. G still needs 300? Wait, demand total 2500, supply 2200 → unbalanced problem (demand > supply). Add dummy source (say Dummy X with supply=300) with zero cost to all destinations.

Revised Allocation (with dummy):

• After step 4: B-G=100, B supply=0.

• C supply=500, G demand=300, F demand=500.

• Allocate C→G: min(500,300)=300 → C-G=300.

• Update: C supply=200, G demand=0.

• Allocate C→F: min(200,500)=200 → C-F=200.

• Update: C supply=0, F demand=300.

• Dummy X supply=300 → allocate to F (or any) with cost 0 → X-F=300.

• All demands satisfied.

Final Allocation Table:

Total Cost Calculation:

= (A-H: 800×3) + (B-D: 400×4) + (B-G: 100×6) + (C-E: 400×4) + (C-F: 200×6) + (C-G: 300×6) + (X-F: 300×0)

= 2400 + 1600 + 600 + 1600 + 1200 + 1800 + 0

= ₹9200

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Exam Must: Always check if total supply = total demand. If not, add dummy row/column with zero cost. Show allocation step-by-step.

VI. INVENTORY MANAGEMENT

Economic Order Quantity (EOQ) Model

Assumptions:

• Demand rate constant & known (D units/year).

• Lead time constant & known.

• Ordering cost (S) per order fixed.

• Holding/carrying cost (H) per unit per year constant (usually % of unit cost).

• No stockouts (backordering not allowed).

• Instantaneous replenishment (order arrives all at once).

Derivation (Concept):

Total Annual Cost (TC) = Ordering Cost + Holding Cost + Material Cost.

• Ordering Cost = (D/Q) × S

• Holding Cost = (Q/2) × H

• Material Cost = D × C (C = cost per unit)

Minimize TC by differentiating w.r.t Q and setting to zero:

$$ \frac{d(TC)}{dQ} = -\frac{DS}{Q^2} + \frac{H}{2} = 0 $$

$$ \Rightarrow \frac{DS}{Q^2} = \frac{H}{2} $$

$$ \Rightarrow Q^2 = \frac{2DS}{H} $$

$$ \boxed{EOQ = Q^* = \sqrt{\frac{2DS}{H}}} $$

Total Minimum Cost:

$$ \boxed{TC_{min} = \sqrt{2DSH} + DC} $$

Inventory Classification

Application: ABC → frequent review, accurate records for A items. VED → high safety stock for V items. FSN → dispose N items.

Reorder Point and Inventory Levels

Reorder Point (ROP): Inventory level at which a new order is placed.

$$ \boxed{ROP = (Demand\ per\ day \times Lead\ time\ in\ days) + Safety\ Stock} $$

• Demand per day = Annual Demand / Working days per year.

• Safety Stock = Buffer for demand/lead time uncertainty.

Inventory Levels (for constant demand, order quantity Q):

• Maximum Inventory = Q + Safety Stock (just after order arrival).

• Minimum Inventory = Safety Stock (just before order arrival).

• Average Inventory = (Maximum + Minimum)/2 = Q/2 + Safety Stock.

Quantity Discounts and EOQ

Types:

1. All-units discount: Discount applies to entire order if quantity ≥ breakpoint.

2. Incremental discount: Discount applies only to units above each breakpoint.

Procedure to Evaluate:

1. Compute EOQ without discount (using regular cost C).

2. If EOQ < discount breakpoint, compute Total Cost at EOQ (using regular C).

3. Compute Total Cost at each breakpoint ≥ EOQ (using discounted C for all units in all-units; incremental for incremental).

4. Choose quantity with lowest total cost.

Example (from May 2024 paper):

• D=24,000 units/year, C=Rs.1.25/unit, S=Rs.22.5, H=5.4% of C = 0.054×1.25 = Rs.0.0675/unit/year.

• EOQ = √(2×24000×22.5 / 0.0675) = √(1,080,000 / 0.0675) = √16,000,000 = 4000 units.

• TC at EOQ = √(2×24000×22.5×0.0675) + 24000×1.25 = √(86,400) + 30,000 = 293.94 + 30,000 = Rs.30,293.94.

• Discount offer: 5% on single order of 24,000 units → New C = 1.25×0.95 = Rs.1.1875.

  • If order 24,000 units: Ordering cost = 1×22.5 = 22.5; Holding cost = (24000/2)×0.054×1.1875 = 12000×0.064125 = Rs.769.50; Material cost = 24000×1.1875 = 28,500.

  • TC = 22.5 + 769.50 + 28,500 = Rs.29,292.

• Decision: Since 29,292 < 30,293.94, accept discount if ordering 24,000 units is feasible (storage, cash flow).

Additional parts from paper:

• Working days = 300 → Daily usage d = 24000/300 = 80 units/day.

• Lead time L = 12 days, Safety Stock SS = 400 units.

• ROP = 80×12 + 400 = 960 + 400 = 1360 units.

• Minimum Inventory = SS = 400 units.

• Maximum Inventory = Q + SS = 4000 + 400 = 4400 units.

• Average Inventory = Q/2 + SS = 2000 + 400 = 2400 units.

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Common Error: Forgetting to include material cost in TC for discount comparison. Always compute full TC = Ordering + Holding + Material.

VII. ADVANCED PLANNING SYSTEMS

Manufacturing Resources Planning (MRP II)

Definition: An integrated, computer-based system that expands MRP to include capacity planning, shop floor control, and financial planning. It links all manufacturing functions (production, inventory, purchasing, finance) into a unified plan.

Components:

1. Business Planning → 2. Production Planning → 3. Master Production Schedule (MPS) → 4. MRP (explodes BOM) → 5. Capacity Requirements Planning (CRP) → 6. Shop Floor Control → 7. Performance Measurement (with feedback loops).

Common Failures/Limitations:

• Data Integrity: Garbage in, garbage out. Inaccurate inventory/BOM.

• Ignoring Capacity: MRP assumes infinite capacity; CRP often not properly implemented.

• Rigidity: Difficult to handle frequent changes (e.g., rush orders).

• Implementation Cost/Time: Expensive, lengthy, requires cultural change.

• Over-reliance: Treats system as "magic black box" without understanding logic.

• Poor Integration: Standalone modules, not truly integrated with finance/accounting.

Enterprise Resource Planning (ERP)

Definition: Cross-functional, integrated software that manages all business processes (production, finance, HR, sales, procurement) across the entire enterprise using a centralized database.

Advantages:

• Single database → data consistency, real-time information.

• Improved coordination between departments.

• Better customer service (order tracking).

• Standardized processes, reduced paperwork.

• Supports strategic decision-making with integrated data.

Disadvantages:

• Very high cost (software, hardware, consulting, training).

• Long implementation time (1–3 years).

• Business process reengineering required → resistance to change.

• Customization can be complex/expensive.

• Requires top management commitment.

Implementation Phases (Typical):

1. Pre-evaluation & Planning: Define objectives, select software/vendor, form team.

2. Business Process Reengineering (BPR): Analyze & redesign processes to fit ERP "best practices".

3. Project Design: Detailed planning, gap analysis, customization specs.

4. Development & Configuration: Set up modules, develop custom interfaces/reports.

5. Testing: Unit, integration, user acceptance testing (UAT).

6. Training: End-users, IT staff.

7. Deployment & Go-Live: Data migration, cutover from old systems.

8. Post-Implementation Support: Troubleshooting, optimization, audits.

Critical Success Factors:

• Top management commitment & sponsorship.

• Clear objectives & scope.

• Effective project management.

• User involvement & training.

• Data accuracy & migration.

• Change management & communication.

• Realistic timeline & budget.

VIII. PRODUCTIVITY MANAGEMENT

Role of Factory Executives and Workers

Factory Executives (Management):

• Set Vision & Goals: Define productivity targets aligned with business strategy.

• Provide Resources: Invest in modern machinery, tools, technology.

• Design Efficient Systems: Implement PPC, MRP, lean methods, ergonomic workplaces.

• Training & Development: Upskill workers for multi-tasking, problem-solving.

• Motivation & Incentives: Link rewards to productivity gains (e.g., gainsharing).

• Worker Involvement: Establish suggestion schemes, quality circles, Kaizen teams.

• Measure & Monitor: Track productivity metrics (output/input), analyze variances.

• Remove Obstacles: Address bottlenecks, material shortages, equipment downtime.

Workers:

• Skill Mastery: Perform tasks efficiently, suggest improvements.

• Adherence to Standards: Follow standard methods, reduce waste.

• Proactive Problem-Solving: Report issues early, participate in continuous improvement.

• Teamwork: Collaborate, share knowledge, support colleagues.

• Safety & Care: Maintain equipment, avoid accidents/downtime.

• Innovation: Contribute ideas via suggestion systems.

Integrated Approach (e.g., Toyota Production System):

• Management provides framework (lean tools: 5S, JIT, TQM).

• Workers execute and improve processes daily (Kaizen).

• Mutual Trust: Respect, open communication, shared benefits.

• Long-term Focus: Invest in people (training) alongside technology.

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Exam Angle: "Role of executives" = strategic, system-level. "Role of workers" = operational, execution-level. Integration = participative management (quality circles, teams).

ADDITIONAL PAST PAPER TOPICS (Brief Notes)

Market Analysis (7m)

Systematic study of market size, trends, customer needs, competition. Methods: Surveys, trend extrapolation, test marketing, economic indicators. Use in PPC: Provides external demand data for sales forecasting, helping set realistic MPS and capacity plans. Without it, forecasts are based only on internal history → risk of market changes.

Synthesis from Standard Data (7m)

Procedure:

1. Break job into standard elements (e.g., "drill hole," "tighten nut").

2. For each element, find standard elemental time from database (adjusted for variables like material hardness, tool diameter).

3. Sum elemental times.

4. Add allowances (personal, fatigue, delay) to get standard time. Example: Element "drill 10mm mild steel" = 0.25 min (from standard data). Job has 4 such holes → 1.0 min. Add 15% allowance → Standard time = 1.15 min. Advantage: Faster than time study for repetitive tasks.

MPS - Master Production Schedule (7m)

Definition: Time-phased plan of end-items to be produced. Inputs: Forecast, orders, inventory, capacity. Outputs: Planned quantity per week for each SKU. Purpose: Drives MRP, communicates to all departments. Key: Must be realistic (feasible with capacity). Changes require replanning.

Inventory Classification (7m)

ABC Analysis: Classify by annual usage value (A=high value, tight control; B=medium; C=low value, simple control).
VED Analysis: Vital (stock always), Essential (stock but can delay), Desirable (stock minimal). For spare parts.
FSN Analysis: Fast movers (review often), Slow movers (review less), Non-movers (dispose).
Application: Prioritize management effort—A/V/F items get most attention (frequent review, accurate records, high safety stock).

Final Note: This unit is calculation-heavy (EOQ, Transportation, ROP, Line Balancing). Practice numerical problems from past papers. For theory, focus on definitions, comparisons, procedures, advantages/disadvantages. Always link concepts to real manufacturing scenarios.