(KMBNOM02) Unit 2: Process of Production Planning and Control

Process of Production Planning and Control

Production Planning and Control (PPC) is like organizing and managing a kitchen to prepare meals efficiently. Let’s break it down in simple terms with an example:

1. Planning: Deciding What to Make and How to Make It

In a kitchen, you start by planning what dishes you’ll cook. Similarly, in production planning, companies decide what products to make, how much to make, and what materials are needed. They also plan the steps and sequence of operations, just like deciding the steps for cooking each dish. Example: If a bakery plans to make 100 cakes, they decide what ingredients are needed (flour, sugar, eggs), how many bakers are required, and the steps (mixing, baking, decorating) needed to prepare them.

2. Routing: Choosing the Path for Each Step

Routing is like setting a path or sequence for each task, and deciding where each step will take place. In production, it determines the flow of materials and processes to ensure work progresses smoothly. Example: In the bakery, routing decides where mixing, baking, and decorating will happen, ensuring cakes move from one step to the next without delay.

3. Scheduling: Setting the Timeline

This is about timing—just like deciding when to start cooking each dish so everything is ready on time. Scheduling ensures each task starts and finishes on time so that the whole production is completed by the deadline. Example: If cakes need to be ready by 5 PM, scheduling decides when mixing should start, when baking should happen, and when decoration should be done to meet this deadline.

4. Dispatching: Getting Things Started

Dispatching is like giving the green light to start each step. It involves issuing orders, assigning people to tasks, and ensuring all materials are ready. Example: In the bakery, dispatching is like telling the bakers to start mixing ingredients, then baking, then decorating as per the plan.

5. Follow-Up and Control: Checking and Adjusting

Follow-up is about monitoring progress, like a chef checking if all dishes are on track and tasting them to ensure quality. If any step is delayed or there’s a quality issue, adjustments are made. Example: If a cake isn’t baking properly, the bakery might need to increase oven time or change the process slightly to ensure all cakes meet the same standard.

In Short, Production Planning and Control ensures that products are made on time, with the right resources, and meet quality standards. It’s like managing a well-organized kitchen where each task has a place, time, and purpose to deliver a perfect meal (or product) efficiently.

Capacity planning

Capacity Planning is about making sure that a business has the right amount of resources—like people, machines, or materials—to meet its production needs. It’s like deciding how big your kitchen and team need to be to handle a certain number of meal orders.

What is Capacity Planning?

Capacity planning in operations is about calculating and managing how much a business can produce within a certain time, given its resources. It helps companies avoid situations where they have too much or too little capacity to meet demand.

Why is it Important?

Imagine a restaurant where, on some days, they have too few chefs, and customers wait a long time for their food. On other days, they have extra chefs, but not enough orders to keep everyone busy. Capacity planning prevents these issues by matching resources to the expected demand.

Steps in Capacity Planning with an Example

• Forecasting Demand: Estimating the need for products or services. In a restaurant, the owner might predict how many customers will come in each day based on trends, like more people coming in on weekends.
• Evaluating Current Capacity: Checking the existing resources. The restaurant owner assesses how many chefs, kitchen space, and ovens they currently have and whether they can handle the number of expected orders.
• Planning for Additional Resources (or Scaling Down): Deciding if changes are needed to meet demand. If more customers are expected than the kitchen can currently handle, the owner may need to hire more chefs, add cooking stations, or invest in additional ovens.
• Implementing Adjustments: Adding or reducing resources based on needs. If it’s expected that business will be slower during weekdays, the restaurant might schedule fewer chefs on those days to avoid idle staff.

Example: Imagine a bakery that produces 500 loaves of bread daily, but on weekends, demand spikes to 800 loaves. Through capacity planning, they recognize this spike and decide to:

• Schedule extra bakers for weekends.
• Adjust oven timing to maximize output.
• Purchase additional raw materials ahead of time to avoid last-minute shortages.

Outcome of Capacity Planning

With effective capacity planning, the bakery can meet high weekend demand without delays or shortages, while avoiding unnecessary costs during slower days.

In Short, Capacity Planning in operations ensures a business has just the right resources to meet demand—no more, no less. It’s like managing a kitchen’s size and staff so it can handle busy nights and slow afternoons smoothly, ensuring efficiency and satisfaction for both the business and customers.

Concept 

Capacity Planning is like deciding how big of a setup you need to handle the amount of work you expect. It helps businesses make sure they have the right amount of people, equipment, or space to handle demand without having too much or too little.

Think of Capacity Planning Like a Pizza Restaurant Imagine you own a small pizza restaurant:

• Understanding Demand: You first need to know how many pizzas customers want each day. On weekdays, maybe it's around 50 pizzas, but on weekends, it jumps to 100 pizzas. Knowing this helps you see how busy you’ll be.
• Checking Your Current Capacity: Now, look at what you have: Two ovens that can cook 10 pizzas each hour. A staff of 5 people to handle orders, prepare pizzas, and clean up. With your current setup, you can make 80 pizzas in an 8-hour shift. But on weekends, when the demand is 100 pizzas, your current capacity may fall short.
• Planning for Extra Capacity: You need to make changes to meet weekend demand. You might: Add an extra oven or keep the restaurant open for more hours. Hire an extra person to help during busy hours. Pre-make some dough so you can prepare pizzas faster.
• Making Adjustments Based on Demand: By preparing for high demand days, you can meet customer needs without long waits. And during slower days, you don’t have extra ovens or too many employees sitting idle.

Capacity Planning is about finding the right balance: having just the right amount of resources to meet demand without overdoing it. It helps businesses avoid being overwhelmed on busy days and wasteful on slow days.

Types

Capacity Planning helps businesses ensure they have the right amount of resources to meet demand. There are three main types of capacity planning: Lead Capacity Planning, Lag Capacity Planning, and Match Capacity Planning. Let’s look at these with simple explanations and examples.

1. Lead Capacity Planning:Lead Capacity Planning is when a business increases its capacity before demand goes up. It’s a proactive approach that helps them prepare for expected growth. Example: Imagine a toy company knows demand for toys spikes during the holiday season. By October, they start hiring extra workers and ordering more raw materials, even though it’s not yet December. They’re planning ahead so they’ll have enough toys ready when holiday demand hits.

Lead Capacity Planning ensures you’re ready to handle future demand without delays. However, if demand doesn’t increase as expected, you could end up with extra resources you don’t need.

2. Lag Capacity Planning :Lag Capacity Planning is when a business only adds capacity after demand has already increased. This is a reactive approach that minimizes the risk of having too much capacity. Example: A coffee shop notices a steady increase in customers over several weeks. Only once they are sure the demand is consistently higher, they decide to hire an extra barista or buy another coffee machine. They’re waiting to be sure they need the extra help before investing in it.

Lag Capacity Planning is cost-efficient because you’re not investing in new resources until you’re sure they’re necessary. But if demand grows quickly, you might struggle to keep up, which could lead to longer wait times for customers.

3. Match Capacity Planning: Match Capacity Planning is a balanced approach where a business adds small amounts of capacity in response to gradual demand changes. It’s a step-by-step approach to meet demand without overcommitting resources. Example: A bakery notices that sales go up by a few dozen cakes each month. Instead of hiring a lot of extra staff or buying several ovens at once, they hire one part-time baker and add a small oven. They continue adjusting as demand grows steadily, so they’re never over or under-prepared.

Match Capacity Planning is flexible and helps a business keep up with slow but steady demand changes. It reduces the risk of having too much or too little capacity, but it requires careful monitoring of demand trends.

4. Adjustment Capacity Planning: Adjustment Capacity Planning involves making small changes in resources to deal with unexpected demand shifts or seasonal peaks, without a long-term increase in capacity. Example: A clothing store hires extra temporary staff during the back-to-school season when sales spike. After the season, they let go of the temporary staff and return to their normal capacity.

This method is cost-effective for handling short-term demand spikes, helping businesses avoid overstaffing or overspending on resources during slower periods.

5. Design Capacity PlanningDesign Capacity Planning is about setting up maximum output limits based on the physical and technological capacity of the equipment or systems in place. Example:A factory has machinery that can produce 500 widgets per day. The factory’s design capacity is 500 units daily because the machines simply can’t make more than that without upgrades.

It helps businesses understand the ultimate limits of their resources. If demand consistently approaches this design limit, they may need to invest in new technology or equipment upgrades.

6. Effective Capacity Planning: Effective Capacity Planning focuses on determining the highest output a system can realistically achieve, accounting for potential disruptions like maintenance and staff breaks. Example: If a factory’s machines can theoretically produce 500 units a day, but actual output is closer to 450 due to maintenance and downtime, the effective capacity is 450 units per day.

Effective capacity gives a realistic view of what a system can achieve in real-world conditions, helping in accurate planning and preventing over-promising to customers.

7. Aggregate Capacity Planning: Aggregate Capacity Planning considers the overall capacity needs across all products or services within a certain period, rather than focusing on individual items. Example: A car manufacturer plans its capacity based on total cars needed in a year rather than focusing on each car model. They plan for total capacity based on expected yearly demand and adjust production schedules for each model accordingly.

This type is useful for businesses producing multiple products, allowing them to view capacity in a bigger picture. It helps in aligning production with overall business goals.

8. Short-Term Capacity Planning: Short-Term Capacity Planning addresses immediate or near-term capacity needs, typically covering days, weeks, or months. Example: A supermarket adjusts its checkout staffing for the upcoming holiday weekend. Knowing it will be busier, they schedule additional cashiers to handle the increase in shoppers over just a few days.

This is effective for handling sudden increases or drops in demand, keeping operations smooth without long-term commitments or investments.

9. Long-Term Capacity Planning: Long-Term Capacity Planning focuses on capacity needs over the years. It’s about preparing for big changes like expansion, new products, or major technological upgrades. Example: A tech company planning to release a new product line might decide to build a new production facility. They expect demand to grow steadily over the next few years, so they invest now for long-term capacity growth.

Long-term planning helps businesses prepare for major growth or shifts, preventing bottlenecks and enabling expansion.

Summary of Capacity Planning Types

• Lead Capacity Planning: Increasing capacity before demand spikes, useful for proactive businesses facing seasonal or predictable demand.
• Lag Capacity Planning: Adding capacity after demand rises, useful for cost-conscious businesses that prefer to react to actual demand.
• Match Capacity Planning: Adding capacity in small increments, useful for businesses with steady demand growth looking to stay balanced.
• Adjustment Capacity Planning: Temporary capacity changes for short-term demand.
• Design Capacity Planning: Max output based on physical limits of resources.
• Effective Capacity Planning: Realistic output, accounting for real-world factors.
• Aggregate Capacity Planning: Planning total capacity for multiple products.
• Short-Term Capacity Planning: Immediate adjustments for daily or weekly demand.
• Long-Term Capacity Planning: Strategic planning for future growth or expansion.

Plant Capacity

Plant capacity is simply the maximum amount of products a factory or facility can make within a certain period. It’s like figuring out how much a kitchen can cook in one day based on the size of the kitchen, the equipment, and the number of cooks.

Example of Plant Capacity in Simple Terms: Imagine you own a bakery:

• Equipment and Space: Your bakery has three ovens, a big mixing machine, and a small work area.
• Staff: You have four bakers working 8-hour shifts each day.
• Output: Each oven can bake 20 loaves of bread every hour, so your total baking capacity is: 3 ovens × 20 loaves per hour × 8 hours = 480 loaves per day. This 480-loaf limit is your plant capacity—it’s the most your bakery can produce in a single day with its current setup.

Why Plant Capacity Matters

• Knowing plant capacity helps businesses:
• Meet customer demand without falling short or overproducing.
• Plan resources (like labor and materials) efficiently.
• Decide when to expand or invest in new equipment if demand grows.

Plant Capacity in Practice

If your bakery sees that demand is growing beyond 480 loaves a day, you might need to increase capacity. This could mean buying another oven, hiring more bakers, or even expanding your kitchen space.

So, plant capacity is about the maximum potential output a facility can achieve with its current resources, helping ensure it meets demand without overloading the setup.

Plant capacity can be explored in more depth through different factors and examples that impact how much a facility can produce. Let’s go over additional aspects:

1. Rated Capacity vs. Actual Capacity

• Rated Capacity is the maximum output a plant could produce under ideal conditions.
• Actual Capacity is what it usually produces, accounting for real-life factors like maintenance, worker breaks, and equipment downtime.

Example: If a factory’s rated capacity is 1,000 units per day, but it typically produces only 900 units due to regular maintenance, the actual capacity is 900 units per day.

2. Capacity Utilization

Capacity utilization shows how much of the plant’s total capacity is actually being used. It’s expressed as a percentage.

Example: If your plant has a capacity of 1,000 units daily but only produces 700 units, capacity utilization is: (700 units ÷ 1,000 units) × 100 = 70 %. This tells you that 30% of the capacity is idle or unused.

3. Flexible vs. Fixed Capacity

• Fixed Capacity: Some plants have fixed resources and can’t easily adjust capacity. For example, a specialized car factory might have equipment only for certain models.
• Flexible Capacity: Other plants can adjust their setup to produce different products, like a factory that can switch from making shoes to hats with minor adjustments.

Example: A plant with flexible capacity can quickly adjust its machinery to produce more or fewer units based on demand, while a plant with fixed capacity would struggle to meet changes without adding new equipment or expanding.

4. Economies of Scale

As production volume increases, the cost per unit can decrease, meaning higher production often becomes more efficient. This concept is called economies of scale.

Example: A bottled water factory with a capacity of 10,000 bottles per day may find that producing close to this maximum capacity lowers its costs per bottle, as fixed costs (like rent and salaries) are spread over more units.

5. Bottlenecks

A bottleneck is a point in the production process that slows down overall output. Identifying and addressing bottlenecks is key to maximizing plant capacity.

Example: If a factory can produce 1,000 gadgets daily but the packaging department can only handle 800 gadgets, packaging becomes the bottleneck. To reach full capacity, they might need to add more packaging machines or workers.

6. Short-Term vs. Long-Term Capacity Adjustments

• Short-Term Adjustments: Quick fixes like hiring temporary staff, adding shifts, or renting additional equipment.
• Long-Term Adjustments: Major investments like building an expansion, buying new machinery, or adding a new production line.

Example: A factory that experiences high seasonal demand during holidays might add a night shift as a short-term adjustment. If demand remains high all year, they may invest in more equipment as a long-term solution.

7. Impact of Technology and Innovation

Advances in technology can increase plant capacity without expanding physically. Upgrading machinery, implementing automation, or using advanced planning software can all help a plant produce more efficiently.

Example: A textile factory upgrades its looms to faster, automated models, increasing capacity from 500 to 700 rolls of fabric daily without needing extra space or staff.

8. Capacity Planning and Demand Forecasting

Capacity planning is closely tied to demand forecasting. Businesses use forecasts to decide if they should increase or decrease capacity.

Example: A factory that makes smartphones might see rising demand predictions for the next few years. This could prompt them to expand capacity now to avoid shortages and meet future demand.

Capacity Planning Strategies

Capacity planning strategies are different ways businesses decide how to have the right amount of resources (like staff, equipment, or space) available to meet customer demand. It’s about making sure they don’t have too much (wasting resources) or too little (missing out on sales). Let’s look at some common strategies with simple examples:

1. Lead Strategy : The Lead Strategy is about increasing capacity before demand increases. This is a proactive approach, where businesses plan ahead to make sure they can handle demand when it grows. Example: A toy company knows that toy demand spikes during the holiday season. So, they hire extra workers and buy more materials by October, even though it’s a couple of months before the holiday rush. This way, they’re prepared to handle the high demand when it hits in December.

Pros:

• Reduces risk of not meeting customer demand.
• Builds customer loyalty by always having products available.

Cons:

• Can be risky if demand doesn’t grow as expected, leading to wasted resources.

2. Lag Strategy : The Lag Strategy is about increasing capacity after demand has already increased. It’s a reactive approach, where businesses wait to see the demand before they add resources. Example: A coffee shop notices more customers coming in each week. Instead of immediately adding staff, they monitor demand for a few weeks. Only when they’re sure the increased demand will last, they hire an extra barista to help with the rush.

Pros:

• Cost-effective since you’re only investing when you know it’s needed.
• Reduces the risk of overinvesting in unused resources.

Cons:

• If demand rises too quickly, customers might face delays or limited availability.

3. Match Strategy: The Match Strategy balances between Lead and Lag. It involves adding capacity in small steps as demand gradually increases. This helps businesses stay flexible and grow their capacity steadily. Example: A bakery notices that cake orders are growing slowly each month. Instead of hiring many bakers at once, they start by hiring one part-time baker. As demand continues to rise, they add more part-time workers and eventually, another oven. This way, they can meet demand without overcommitting.

Pros:

• Flexible and allows steady growth with demand.
• Reduces the risk of too much or too little capacity.

Cons:

• Requires constant monitoring to keep up with demand changes.

4. Dynamic or Adjustment Strategy : The Dynamic Strategy is all about flexibility, making frequent, small adjustments in response to changing demand. Businesses using this strategy adapt quickly to seasonal or unexpected changes without permanent capacity changes. Example: A retail store hires extra staff temporarily during the holiday shopping season and reduces staff after the season. This strategy allows them to meet peak demand without keeping extra staff year-round.

Pros:

• Efficient for seasonal or unpredictable demand.
• Minimizes costs by adjusting only when needed.

Cons:

• Requires efficient scheduling and quick hiring/training processes.

5. Subcontracting or Outsourcing Strategy: In this strategy, businesses meet extra demand by outsourcing part of their production to another company. This way, they don’t need to invest in new resources but can still meet customer needs. Example: A clothing brand expects a big increase in demand during summer. Instead of expanding their factory, they contract an outside manufacturer to handle the extra work, helping them meet demand without needing more space or equipment.

Pros:

• Cost-effective for temporary demand spikes.
• Avoids long-term investments in equipment or staff.

Cons:

• Can reduce control over quality and timing.
• Outsourcing costs can be high if used frequently.

6. Hybrid Strategy : The Hybrid Strategy combines two or more of the above strategies to adapt to different demand patterns or business conditions. It’s a flexible approach that tailors capacity planning to specific needs. Example: A car manufacturer might use the Lead Strategy to prepare for new model launches (ensuring capacity is high from the start) but also use the Lag Strategy during normal times, only increasing capacity when demand proves to be stable.

Pros:

• Highly adaptable and can handle complex demand patterns.
• Reduces the risk of over-investing or under-investing.

Cons:

• Requires careful planning and monitoring to implement effectively.

Summary of Capacity Planning Strategies

• Lead Strategy: Increase capacity before demand rises (good for anticipated growth).
• Lag Strategy: Increase capacity after demand has risen (cost-effective but may risk delays).
• Match Strategy: Gradual, small increases in capacity to match steady growth.
• Dynamic Strategy: Flexible, temporary adjustments for seasonal or unpredictable demand.
• Subcontracting Strategy: Outsource production to meet extra demand without long-term investment.
• Hybrid Strategy: Combines different strategies to balance growth and efficiency.

Each strategy has its pros and cons, and the choice depends on the business’s goals, demand patterns, and risk tolerance. By selecting the right approach, businesses can stay prepared, efficient, and responsive to changes in demand.

Routing – procedure

Routing is a key part of production planning and control that determines the most efficient path and steps needed to transform raw materials into finished products. Think of routing as a detailed map for a journey, showing how to get from start to finish in the production process.

Routing in Operation Management and Production Control refers to the process of deciding the path or sequence of steps required to manufacture a product. It’s like creating a map or a guide to ensure production runs smoothly.

What is Routing?

In simple terms, routing outlines:

• What machines or workstations will be used.
• The sequence of operations (the order in which tasks will be done).
• The time each step will take.
• The materials needed at each stage.

Example of Routing in a Bakery, Let’s consider a bakery that produces loaves of bread. Here’s how routing would work:

Start with Raw Ingredients: The bakery needs flour, yeast, water, and salt.

Routing Steps:

Step 1: Mixing: 

• The first step is to mix the flour, yeast, water, and salt together. This happens in a mixing machine.
• Time: 15 minutes.

Step 2: Kneading: 

• After mixing, the dough needs to be kneaded to develop gluten. This also happens in a machine specifically for kneading.
• Time: 10 minutes.

Step 3: Rising: 

• The dough needs to rise to allow it to expand. This is done in a proofing chamber.
• Time: 60 minutes.

Step 4: Shaping: 

• After rising, the dough is shaped into loaves by hand or with a shaping machine.
• Time: 10 minutes.

Step 5: Baking:

•  Finally, the loaves are baked in the oven.
• Time: 30 minutes.

Step 6: Cooling:

• After baking, the loaves must cool before packaging.
• Time: 20 minutes.

Routing Summary: The bakery follows this sequence: Mixing → Kneading → Rising → Shaping → Baking → Cooling. The bakery can use this routing to estimate how long it will take to produce a batch of bread and ensure that all equipment and materials are ready for each step.

Why is Routing Important?

• Efficiency: Proper routing helps to minimize time and resource waste by clearly defining each step and its order.
• Predictability: It allows the bakery to predict production times, helping with planning and scheduling.
• Quality Control: By standardizing processes, routing helps maintain consistent product quality.

Summary of Routing Procedure

• Identify Raw Materials: Know what you need to start with.
• Determine Steps: Lay out all the steps in the production process.
• Sequence the Steps: Put the steps in the order they need to be completed.
• Estimate Time for Each Step: Understand how long each operation will take.
• Document the Process: Create a routing guide or document that outlines this process for future reference.

Example in Other Industries

• Manufacturing Cars: In a car factory, routing would include steps like assembling the chassis, installing the engine, painting, and quality checks, with specific machines and workers assigned to each task.
• Textile Production: In a textile factory, routing would cover spinning yarn, weaving fabric, dyeing, and finishing, detailing which machines are used and the order of operations.

Routing is essential in ensuring that production runs smoothly and efficiently, leading to better use of time and resources, and ultimately, higher quality products.

Materials Flow Patterns 

Materials Flow Patterns refer to the way materials move through a production system, including how they are received, processed, and delivered. Understanding these patterns helps businesses organize their production processes efficiently.

Production Scheduling is a critical part of materials flow patterns. It involves planning and organizing when and how much product will be produced, ensuring that resources are used effectively and deadlines are met.

Key Concepts of Materials Flow Patterns and Production Scheduling

• Flow of Materials: This is the journey materials take from the moment they arrive at the factory until they are transformed into finished products.
• Scheduling: This is the timetable that outlines when each step in the production process will take place, including which resources (machines, workers) will be used at each stage.

Example of Materials Flow Patterns and Production Scheduling in a Furniture Factory

Let’s consider a furniture factory that makes wooden tables. Here’s how materials flow patterns and production scheduling would work:

Step 1: Materials Arrival

• Incoming Materials: The factory receives shipments of wood, glue, screws, and varnish.
• Storage: These materials are stored in the warehouse until needed.

Step 2: Materials Flow

1. Cutting:

• Process: The wood is cut into the necessary sizes for table legs, tops, and supports.
• Scheduling: The cutting machine is scheduled to operate from 8 AM to 10 AM every day.

2. Assembly:

• Process: The cut pieces are assembled into table frames.
• Scheduling: Assembly is scheduled from 10:30 AM to 12:30 PM.

3. Finishing:

• Process: The tables are sanded and varnished for a smooth finish.
• Scheduling: The finishing process is scheduled from 1 PM to 3 PM.

4. Quality Control:

• Process: Each finished table is inspected for quality.
• Scheduling: Quality control happens from 3:30 PM to 4 PM.

Step 3: Delivery

• Completed Products: Once approved, the tables are stored in the finished goods section and scheduled for delivery to customers.
• Scheduling: Deliveries are planned for Tuesday and Thursday mornings based on customer orders.

Importance of Materials Flow Patterns and Production Scheduling

• Efficiency: By clearly defining how materials move and when each production step occurs, factories can avoid delays and reduce wasted time.
• Resource Management: Scheduling ensures that machines and workers are available when needed, preventing bottlenecks (delays caused by too much work at one step).
• Meeting Deadlines: With effective scheduling, businesses can better predict when they will finish products and meet customer deadlines.

Types of Production Scheduling

• Discrete Scheduling: Used for distinct items like furniture, where each unit is separate and can be tracked individually.
• Batch Scheduling: Used when making multiple items at once, like batches of cookies. The schedule is organized based on the amount of time needed for each batch.
• Continuous Scheduling: Used in processes like oil refining where production runs continuously without interruption.

In Short,

• Materials Flow Patterns describe how materials are managed in a production process, from arrival to final delivery.
• Production Scheduling is about planning when each step will happen and making sure resources are available to keep production flowing smoothly.

In our furniture factory example, effective materials flow and scheduling help ensure that wood arrives on time, each step in making the tables is organized, and the finished products are delivered to customers without delays.

Detailed Explanation of Materials Flow Patterns

Materials flow patterns represent the pathways that materials take through the production process. Understanding these patterns helps organizations optimize their operations, reduce waste, and improve efficiency.

Types of Materials Flow Patterns

1. Linear Flow:

Description: Materials move through the production process in a straight line, from one workstation to the next. Example: In a bakery, ingredients are added in a specific order: flour → sugar → eggs → baking → cooling → packaging.

2. Circular Flow:

Description: Materials move in a loop, often returning to the starting point after processing. Example: In a recycling plant, materials are sorted, processed, and returned to a storage area for future use or repurposing.

3. Network Flow:

Description: Materials can flow through multiple paths and can take different routes depending on various factors like machine availability. Example: In a car manufacturing plant, parts can be assembled in different sequences depending on which components are available at that time.

Advanced Scheduling Techniques

Production scheduling is not just about setting a timetable; it involves various techniques to ensure that production runs smoothly and meets customer demands. Here are some advanced techniques:

1. Just-In-Time (JIT) Scheduling:

Description: Aims to reduce inventory costs by scheduling materials to arrive just when they are needed in the production process. Example: An automobile manufacturer orders parts to arrive at the assembly line only when needed, minimizing storage costs.

2. Lean Scheduling:

Description: Focuses on eliminating waste and improving flow in the production process. It often includes techniques like Kanban (a visual scheduling system) to manage work and inventory. Example: A clothing manufacturer uses Kanban cards to signal when to start producing new items based on customer orders.

3. Theory of Constraints (TOC)

Description: This method identifies the biggest bottleneck (constraint) in the production process and focuses on improving that specific area to increase overall output. Example: In a food processing plant, if the packaging machine is the slowest step, TOC would involve optimizing that machine to increase overall production speed.

4. Finite Scheduling

Description: Takes into account the limitations of resources (like machines and workers) when creating a production schedule, preventing overloading of any part of the system. Example: A printing company schedules jobs based on machine availability, ensuring no single printer is overwhelmed with too many orders at once.

5. Master Production Schedule (MPS):

Description: A detailed plan that outlines what products need to be produced, in what quantities, and when. It helps coordinate between different departments. Example: A toy manufacturer creates an MPS for different toy lines, specifying production targets for each month to align with marketing campaigns.

Benefits of Effective Materials Flow and Production Scheduling

• Increased Efficiency: By understanding how materials flow and scheduling correctly, businesses can eliminate unnecessary steps and reduce production time.
• Better Resource Utilization: Effective scheduling ensures that machines and labor are used optimally, avoiding periods of idle time.
• Improved Product Quality: Streamlined processes help maintain consistency, which can enhance product quality and reduce defects.
• Enhanced Customer Satisfaction: Meeting production deadlines and delivering on time leads to higher customer satisfaction and loyalty.
• Cost Reduction: Minimizing waste and optimizing inventory levels can lead to significant cost savings.

Challenges in Materials Flow and Production Scheduling

• Demand Fluctuations: Sudden changes in customer demand can disrupt production schedules and lead to shortages or excess inventory.
• Resource Limitations: Limited availability of machines, labor, or materials can create bottlenecks in the production process.
• Complexity of Operations:In industries with complex supply chains or multiple products, it can be challenging to design an effective materials flow and scheduling system.
• Communication Gaps: Poor communication between departments can lead to misunderstandings about priorities and timelines, affecting overall efficiency.

Industry Examples of Materials Flow Patterns and Scheduling

1. Food Industry:

• Flow Pattern: Ingredients arrive and are processed in a sequential flow (e.g., from receiving to preparation to cooking).
• Scheduling: Food products are often scheduled based on expiration dates, with JIT techniques used to minimize waste.

2. Electronics Manufacturing: 

• Flow Pattern: Components like chips and casings move through multiple workstations in a network flow to allow for flexibility.
• Scheduling: Finite scheduling is crucial to manage the complex assembly process and ensure timely deliveries.

3. Construction:

• Flow Pattern: Materials like bricks, cement, and steel are delivered to the site in stages based on project needs (often a linear flow).
• Scheduling: A master production schedule outlines timelines for various phases of construction to ensure everything is completed on time.

In Short, Materials flow patterns and production scheduling are essential components of efficient manufacturing and production processes. By understanding how materials move through a system and effectively scheduling their use, businesses can optimize operations, reduce costs, and improve product quality. These concepts apply across various industries, each adapting techniques to suit their specific needs and challenges.

Machine Scheduling and Line Balancing with Numerical -Loading 

Machine Scheduling and Line Balancing are important concepts in production management that help optimize the use of machines and workstations to improve efficiency and productivity. Let's break these concepts down into simpler terms, along with examples and numerical illustrations.

Machine Scheduling

Machine Scheduling refers to planning the allocation of machines to tasks over time. It ensures that machines are used effectively without idle time, helping to meet production deadlines.

Example of Machine Scheduling:A small factory has three machines (A, B, and C) that need to complete three different jobs (Job 1, Job 2, and Job 3). The estimated time (in hours) to complete each job on each machine is shown in the table below:

Step 1: Determine Machine Scheduling

To minimize the total processing time, we will select the best machine for each job based on the shortest time.

• Job 1: Choose Machine A (2 hours).
• Job 2: Choose Machine A (1 hour).
• Job 3: Choose Machine B (1 hour).

Step 2: Total Time Calculation

Now, we add the times for each job based on the chosen machines:

• Total time for Machine A: Job 1 (2) + Job 2 (1) = 3 hours
• Total time for Machine B: Job 3 (1) = 1 hour
• Total time for Machine C: No jobs scheduled = 0 hours

Line Balancing

Line Balancing is the process of assigning tasks to workstations in a way that each workstation has an approximately equal amount of work. This helps in reducing idle time and improving efficiency in assembly lines or production processes.

Example of Line Balancing: A production line for assembling bikes has five tasks (T1 to T5) with the following estimated times (in minutes):

Step 1: Calculate Total Time and Cycle Time

• Total time = T1 + T2 + T3 + T4 + T5
• Total time = 5 + 8 + 3 + 7 + 4 = 27 minutes

Desired Cycle Time: If the production line needs to produce 6 bikes per hour, we can calculate the cycle time: Cycle Time = 60 minutes / 6 bikes = 10 minutes per bike

Step 2: Line Balancing

Now we assign tasks to workstations while keeping the cycle time in mind (10 minutes):

• Workstation 1: T1 (5) + T3 (3) = 8 minutes
• Workstation 2: T2 (8) + T5 (4) = 12 minutes (Too much, so we will adjust)
• Workstation 3: T4 (7) = 7 minutes

To balance the workload, we can redistribute tasks:

• Adjusted Workstation 1: T1 (5) + T3 (3) = 8 minutes
• Adjusted Workstation 2: T2 (8) = 8 minutes
• Adjusted Workstation 3: T4 (7) + T5 (4) = 11 minutes (Still too high)

Final Balanced Workstations

To balance it further, we might have:

• Workstation 1: T1 (5) + T5 (4) = 9 minutes
• Workstation 2: T2 (8) + T3 (3) = 11 minutes
• Workstation 3: T4 (7) = 7 minutes

Now we can adjust the workstations further to achieve closer times to the 10-minute target.

Numerical Loading Process

Loading is the process of assigning jobs or tasks to machines or workstations based on their capacity and availability.

Example of Loading: Suppose we have two machines (M1 and M2) with the following capacities:

• Machine M1: Capacity = 10 hours
• Machine M2: Capacity = 8 hours

And we have the following jobs to complete:

Step 1: Assign Jobs to Machines

• Assign Job 1 (4 hours) to Machine M1. Remaining capacity for M1 = 10 - 4 = 6 hours.
• Assign Job 2 (3 hours) to Machine M1. Remaining capacity for M1 = 6 - 3 = 3 hours.
• Assign Job 3 (2 hours) to Machine M2. Remaining capacity for M2 = 8 - 2 = 6 hours.
• Assign Job 4 (5 hours) to Machine M1 (not enough capacity). It will go to Machine M2, but it can only take 6 hours.
• Remaining capacity for M2 after Job 4 = 6 - 5 = 1 hour (so, not feasible).

We can reassign and prioritize jobs based on deadlines or importance, leading to another cycle of loading decisions.

In Short,

• Machine Scheduling: Plan and allocate jobs to machines based on processing times to minimize idle time and ensure timely completion.
• Line Balancing: Assign tasks to workstations so that each has an approximately equal amount of work, improving efficiency.
• Loading: Assign jobs to machines or workstations based on their capacity and availability, ensuring efficient use of resources.

By managing machine scheduling, line balancing, and loading effectively, organizations can optimize their production processes, improve output, and reduce costs.

Strategies and Relationship between Capacity and Loading

The concepts of capacity and loading are fundamental to managing production effectively. In simple terms:

• Capacity is how much work a machine, employee, or production line can handle in a certain period.
• Loading is the process of assigning specific tasks or jobs to that capacity.

The Relationship between Capacity and Loading

• Capacity Determines Limits for Loading: The capacity of a machine or production line sets the maximum amount of work it can handle. So, loading has to fit within that capacity limit to avoid overloading, which can lead to delays and inefficiency.
• Loading Utilizes Capacity: Effective loading ensures that a machine's or employee's capacity is fully used without being overburdened or left idle. Matching capacity with loading helps in achieving a balanced workflow and avoiding bottlenecks.
• Matching Strategy: Companies often plan capacity based on expected loading needs. For example, if a company knows it has to produce a high volume in the future, it may expand its capacity by adding more machines or hiring more staff to match the loading requirements.

Let’s dive into strategies and examples to understand these ideas better.

Strategies for Matching Capacity and Loading

• Chase Strategy: Adjust capacity to match demand. For instance, if more products are needed, capacity is increased by adding shifts or machines. When demand falls, capacity is reduced. Example: A bakery hires temporary staff during holiday seasons to keep up with extra demand but reduces staff after the holidays.
• Level Production Strategy: Keep capacity constant and try to smooth out demand by having a consistent workload. Example: A car manufacturer produces a steady number of cars every month, regardless of demand fluctuations, and stocks the cars for when demand increases.
• Subcontracting: When demand exceeds capacity, companies may subcontract work to third parties to meet the loading requirements without expanding in-house capacity. Example: A clothing brand outsources excess production during peak seasons to other factories to handle additional orders.
• Hybrid Strategy: Combines elements of chase and level strategies. Capacity is adjusted partially in response to demand but within limits. Example: An electronics manufacturer adds some temporary workers and increases machine hours during high demand but doesn’t overinvest in permanent capacity.

Numerical Example of Capacity and Loading

Suppose a factory has two machines, each with a daily capacity of 8 hours (or 480 minutes). The factory needs to complete four jobs, each with its required processing time.

Total Capacity Available: Each machine can work for 480 minutes per day. With two machines, the total daily capacity is: 480 minutes × 2=960 minutes

Total Loading Requirement: To find if the jobs fit within the available capacity, add up the time needed for each job: 200+300+100+250=850 minutes

Capacity Utilization: 850/960 × 100 = 88.54 %

This means 88.54% of the total capacity will be utilized by these jobs.

Example of Capacity and Loading Assignment

Now, let’s see how we can assign jobs to the two machines without overloading either one.

Machine 1: Assign Job 1 (200 minutes) and Job 3 (100 minutes).
Total time for Machine 1 = 200 + 100 = 300 minutes.
Capacity Utilization for Machine 1 =  300/480 ×100 = 62.5 %

Machine 2: Assign Job 2 (300 minutes) and Job 4 (250 minutes).

Total time for Machine 2 = 300 + 250 = 550 minutes.

Since Machine 2 has only 480 minutes of capacity, it would be overloaded by 70 minutes.

Adjustments

To balance the load: We could try redistributing by moving Job 4 to Machine 1, making both machines closer to capacity:

Machine 1: 200 (Job 1) + 250 (Job 4) = 450 minutes, Capacity Utilization =  450/480 ×100=93.75%

Machine 2: 300 (Job 2) + 100 (Job 3) = 400 minutes, Capacity Utilization = 400/480×100=83.33 %

In Short,

• Capacity sets the boundary for how much work can be loaded onto machines.
• Loading utilizes capacity by assigning jobs to machines within those boundaries.

Balancing loading across machines avoids overloads and idle times, maximizing productivity.

In this example, understanding capacity and loading helped us reassign jobs efficiently so that both machines are well-utilized without overloading.

PPC in different Production Systems 

Production Planning and Control (PPC) helps manage and streamline production in different production systems like job, batch, mass (assembly), and continuous production. Let’s break down how PPC works in each system with examples.

1. Job Production System

In Job Production, each product is custom-made based on specific customer requirements. This system is used for unique, single items that are typically produced one at a time. Example: Custom furniture manufacturing, where each piece of furniture is crafted individually to meet the client's specifications.

PPC in Job Production

• Planning: PPC plans each job separately, as each one is unique. This includes understanding the client’s specifications, creating a design, and scheduling tasks based on individual requirements.
• Control: PPC ensures each step is completed according to the client's specifications and deadlines. Since jobs are customized, PPC must monitor each stage closely.

Key Focus: Customization, scheduling for individual tasks, quality control.

2. Batch Production System

In Batch Production, products are made in batches or groups, where a specific quantity of the same product is produced before moving on to a new batch. This system is useful when demand for a product varies or when producing multiple similar items. Example: A bakery producing batches of 100 cupcakes of the same flavor before switching to a different flavor.

PPC in Batch Production

• Planning: PPC plans for each batch, including deciding batch size, ordering materials in the correct quantities, and scheduling production time.
• Control: PPC monitors each batch for consistency, ensuring that all items in the batch meet quality standards. It also checks that production switches smoothly from one batch to another.

Key Focus: Consistency within batches, managing changeovers, inventory control.

3. Mass (Assembly) Production System

Mass Production (also known as assembly production) is a system where large volumes of standardized products are produced, often on an assembly line. This approach is common for items with high demand, where products are similar and made quickly. Example: Car manufacturing, where thousands of cars of the same model are produced on an assembly line.

PPC in Mass Production

• Planning: PPC focuses on creating a highly efficient, repeatable process. This involves planning assembly line steps, minimizing downtime, and ensuring each step has the necessary materials and labor.
• Control: PPC monitors the assembly line to ensure production moves smoothly and that no step holds up the line. Quality control checks are done throughout to ensure all products meet standards.

Key Focus: Efficiency, minimizing production delays, quality consistency.

4. Continuous Production System

In Continuous Production, production runs non-stop, 24/7. It’s used for products that are always in demand and are produced on a large scale, like chemicals, oil, and electricity. The production line doesn’t stop, and the process is highly automated. Example: An oil refinery that continuously processes crude oil into gasoline.

PPC in Continuous Production

• Planning: PPC plans for a steady flow of materials and ensures machines run continuously. Since it’s automated, PPC sets production targets and schedules maintenance to prevent downtime.
• Control: PPC monitors the production process to catch any issues quickly. Continuous production also involves a lot of quality monitoring since one interruption could affect large volumes of product.

Key Focus: Maintaining uninterrupted production, high automation, regular maintenance.

In each system, PPC tailors its approach to fit the specific production style, ensuring that materials, machines, and labor are used efficiently to meet demand and maintain quality.

Unit -1 Introduction of Operation Planning & Control | Unit 3: Aggregate Planning