The economy is moving faster and faster, and production is increasingly becoming a matter of time and cost management. However, when working at the limit, it’s not easy to understand how to allocate resources, and often there’s no time for reasoning. This is where production planning software comes to our rescue.
A definition
Industrial scheduling refers to the process of organizing, planning, and optimizing production activities. The goal is to maximize efficiency, reduce costs, and improve the quality of the final product. It’s a complex objective that aims at the company’s well-being.
Types of scheduling
1. Forward incremental scheduling
This method, developed in the 1960s as part of project management techniques, starts from the beginning of the production process and plans activities in chronological order.
Origins: Forward incremental scheduling was formalized by James E. Kelley and Morgan R. Walker as part of the Critical Path Method (CPM).
Applicability: It’s particularly suitable for industries with linear and predictable processes, such as the production of electronic components or automobile assembly.
Pros:
- Simple to implement and understand
- Effective for projects with well-defined activity sequences
Cons:
- Doesn’t account for potential resource conflicts along the production line
- Can lead to downtime if not managed correctly
Examples of Companies: Toyota has used this technique as part of its Just-In-Time production system.
2. Backward incremental scheduling
This method, which emerged in the 1970s as an evolution of forward scheduling, starts from the delivery date and plans activities backwards.
Origins: Backward scheduling was developed in the field of supply chain management, particularly with the advent of Material Requirements Planning (MRP) systems.
Applicability: It’s particularly useful for companies working with perishable products, industries with rigid delivery dates, or those with storage limitations.
Pros:
- Optimizes inventory management
- Reduces storage costs
- Particularly effective for make-to-order production
Cons:
- Can be complex to implement in highly articulated production processes
- Requires accurate prediction of production times
Examples of Companies: Dell Computer has used this technique for its customized PC production.
3. Chase production scheduling
This approach, born in the 1980s with the advent of lean production, adapts production directly to market demand.
Origins: Chase production scheduling was theorized by Taiichi Ohno as part of the Toyota Production System.
Applicability: It’s ideal for companies with limited economic capacity, operating with short-lived goods or in highly volatile markets.
Pros:
- Minimizes excess inventory
- Improves responsiveness to market fluctuations
- Optimizes resource use
Cons:
- Requires great production flexibility
- Can lead to higher costs due to frequent production changes
Examples of Companies: Zara uses this approach in the fast-fashion industry.
4. Infinite capacity scheduling
This traditional method, used since the dawn of industrial production, attempts to adapt demand to the company’s maximum production capacity.
Origins: Infinite capacity scheduling is a concept dating back to the era of mass production, formalized in Frederick Taylor’s early studies on scientific work organization.
Applicability: It’s still common in many manufacturing companies, especially those with stable production processes and predictable demand.
Pros:
- Simple to implement without advanced IT tools
- Maximizes the use of production resources
Cons:
- Can lead to inefficiencies and waste
- Doesn’t take into account the real limits of production capacity
Examples of Companies: Many companies in the steel industry still use this approach.
5. Finite capacity scheduling
Using advanced technologies, this method considers all production factors to optimize planning.
Origins: Finite capacity scheduling emerged in the 1990s with the advent of advanced computer systems and Industry 4.0.
Applicability: It’s particularly suitable for companies that have embraced digital transformation, operating in highly complex sectors.
Pros:
- Maximizes efficiency by considering multiple variables
- Allows dynamic and real-time planning
- Reduces downtime and optimizes resource use
Cons:
- Requires significant investments in IT infrastructure
- Needs qualified personnel for management
Examples of Companies: Siemens has implemented this approach in its smart factories.
6. Make-to-stock
This approach, based on inventory management theories developed in the 1950s, relies on forecasting cyclical demand.
Origins: The concept of Make-to-Stock was formalized by scholars such as Harold Bright Maynard in the field of industrial management.
Applicability: It’s suitable for companies producing standardized goods with stable and predictable demand.
Pros:
- Allows quick response to demand during peak periods
- Optimizes production costs through economies of scale
Cons:
- Requires good market knowledge and predictive capabilities
- Risk of inventory obsolescence
Examples of Companies: Procter & Gamble uses this approach for many of its consumer products.
7. Make-to-order
In this model, production is initiated only after receiving a specific order from the customer.
Origins: Make-to-Order is a concept as old as craftsmanship, but it was formalized as an industrial strategy in the 1980s with the advent of mass customization.
Applicability: It’s ideal for companies offering highly customized or luxury products.
Pros:
- Minimizes inventory and customizes the product
- Reduces risks of overproduction
- Improves customer satisfaction
Cons:
- Can lead to longer delivery times
- Requires flexible production management
Examples of Companies: Boeing uses this approach for the production of commercial aircraft.
How to choose?
The choice of the most suitable scheduling method depends on various factors, including the nature of the business, the size of the company, and the characteristics of the target market. Many successful companies adopt hybrid approaches, combining different strategies to optimize their production processes.
