In successful factories, everything every employee does is, in some way, determined by the production schedule. Whether you work in Manufacturing Engineering, Quality, Production or anywhere in the supply chain, understanding how this schedule is created and what it does will help you do your job better.
The production scheduling process produces a dynamic schedule that is continuously updated as orders are completed, new orders and materials arrive, and conditions on the factory floor evolve.
Production scheduling entails planning, organizing and assigning resources (machines, labor, and materials) to complete production tasks efficiently. Think of it as the process of deciding how and when each order will be made and what resources will be used.
Effective production scheduling aligns capacity with demand, delivery deadlines and available resources. It’s essential for reducing bottlenecks, ensuring production efficiency and meeting customer expectations. When scheduling is not well-managed, it can lead to underutilized machines and labor, extended lead times, and elevated inventory levels—ultimately impacting customer satisfaction and business performance.
Every employee plays a role in achieving the schedule. Whether you’re in Maintenance, the Toolroom or Inspection, an understanding of production scheduling will help you maximize the value of your contribution.
Goals and benefits of production scheduling
The goal of scheduling is to have a plan that shows how customer orders will be satisfied. This covers the sequence in which orders will be released into the factory, the machines, lines and cells they will run through, and the materials and labor needed. The schedule in effect makes it clear what each employee should be doing to achieve the goals of the organization. The reasons for production scheduling are:
- Ensure on-time delivery and optimize workflow: Scheduling includes order prioritization and lead time estimation.
- Balance workload across equipment and labor: Work is allocated to machines based on the availability of labor and machine capacity and in a manner that avoids the peaks and troughs that create lead-time variability.
- Minimize downtime, changeovers and inventory carrying costs: Orders are often sequenced in a way that minimizes setup time, and flow is maintained to prevent buildup of Work-in-Process (WIP) inventory.
- Enable accurate forecasting and inventory management: This reduces the risk of overproduction or stockouts, enables planning of raw material purchases and delivery (through integration with the ERP system) and provides visibility of inventory.
- Improve customer satisfaction with reliable lead times: By ensuring stability and predictability throughout production, scheduling eliminates the variability that leads to fluctuations in lead time and the buildup of WIP.
Key elements of a production schedule
The production schedule details what will be produced, when and by whom. It covers the route each order will take through the factory and the raw materials and components or subassemblies to be incorporated. There may also be information on start and/or due dates and relative priorities (“Rush” or “Express” order, for example).
Breaking this down, while plants look for different things in their production schedules, the main elements are:
- Work order information: Details of each product to be made, including quantity and sometimes also the customer reference.
- Task priority and sequence: The product routing outlines the order of each production step. The schedule can add further prioritization information to minimize delays and nonproductive time.
- Machine and labor availability: Links to the routing provide resource allocation information, helping production supervisors coordinate the availability of personnel, including specialists, for the work needed.
- Material availability: Raw materials, components, coating materials and subassemblies are all identified, and links to ERP ensure availability at the time and place needed.
- Time requirements per task: Operation and/or processing times are vital for determining resource utilization and capacity requirements. They also play a key role in load-leveling calculations and related planning activities.
- Dependencies between tasks: The routing establishes the operation sequence, but other dependencies may exist. For example, color or flavor changes may only be done in a specific sequence, or subassemblies may need holding in a particular location or under set conditions for a period.
- Buffer times for maintenance or delays: Equipment is stopped periodically for maintenance and inspection, safety checks may be needed and breakdowns are a possibility.
Common production scheduling techniques
The method or methods a business adopts for scheduling production (it’s possible to use more than one under the same roof) depend on the variety and type of products being manufactured, and whether the business makes to order or for stock. Techniques often used for scheduling production activities are:
- Forward and backward scheduling: The first of these refers to setting the date when the order will be started. The second involves setting a finish by or required by date and working back to determine when to release the order.
- Just-in-time (JIT) scheduling: This seeks to reduce inventory by minimizing inventory buffers and timing the arrival of materials to precisely when they are needed. It saves space and compresses lead time but requires tightly synchronized manufacturing operations.
- Finite vs. infinite capacity scheduling: While capacity is always finite, in all but the least complex flow and process operations, scheduling on this basis has always been extremely difficult. In recent years, increased computational capabilities have enabled finite capacity scheduling, which results in more realistic and achievable schedules.
- Gantt charts and visual scheduling tools: Often used in plants producing large, one-off products, but this approach becomes impractical when the number and variety of products being made increases.
- Heuristic and AI-assisted optimization methods: Scheduling, especially in batch manufacturing, involves navigating a vast number of possible combinations and sequences. To manage this complexity, many teams rely on scheduling heuristics—practical, experience-based rules such as ‘First-In, First-Out’ or ‘Earliest Due Date.’ Some software vendors offer AI-assisted scheduling that builds on past experience to develop better schedules.
- Push vs. pull systems (e.g., Kanban in Lean manufacturing): The traditional, ERP-driven approach is to “push” orders and material into the factory and wait for them to emerge as finished products. Since the 1970s though, pull methods have proven more adept at constraining WIP and synchronizing operations. Typically, this is implemented through “kanbans” or signals that tell an upstream department to deliver product.
Challenges in production scheduling
Efficient production scheduling has always been difficult. Increased computing power and new techniques like kanban help, but most manufacturers still struggle to maintain high levels of schedule adherence.
Three major problems are:
- The computational complexity of the scheduling problem
- Unplanned events, like machine breakdowns
- Unpredictable quality losses
Computational complexity
Scheduling, especially in batch and high-mix, low-volume environments, deals with an immense number of possible permutations and combinations, plus multiple constraints, all while seeking to meet goals that sometimes conflict. (For example, minimizing machine changeovers while also keeping lead times as short as possible.)
This problem quickly overwhelms software-based scheduling tools, hence the use of heuristics and increasingly, AI assistance.
Unplanned events
Production capacity calculations take into account expected events like team meetings, safety briefings and cleaning time. What they can’t consider though, other than by applying broad averages, are unexpected events.
One example, hopefully very rare, is an industrial accident. Two others are machine breakdowns and labor shortages. In each case, production can be stopped, possibly for hours, while corrective actions are taken, and this loss of capacity will put the schedule out. If it’s not possible to catch up, which will need a revised schedule, the customer may have to be notified of late delivery.
Quality losses
The quantity needed is often increased above the number ordered to account for parts used for setup and destructive testing or inspection.
If a quality problem arises and more parts are lost than was anticipated, the manufacturer has two options: ship fewer parts than the customer ordered or issue a second Work Order to make up the number of pieces lost.
Most manufacturers are unwilling to do the first, but the second is extremely disruptive and forces updates to the production schedule.
Role of technology in scheduling optimization
All but the smallest manufacturers use production scheduling software. Typically integrated into ERP and Manufacturing Execution Systems (MES), these scheduling modules handle the challenges of product variety and complex routings, and the pressures on production costs and lead time.
As noted, complexity forces many plants to supplement scheduling with heuristics, resulting in suboptimal resource utilization. To tackle this, AI support for production scheduling is emerging. These systems learn how to optimize production schedules under varying conditions and provide appropriate recommendations to the production control staff.
Now that computers can handle finite capacity planning, the biggest challenge is adapting quickly to changes in the production environment. The risk is that production or material delays, labor shortages or machine breakdowns will leave resources idle while WIP accumulates and orders are shipped late. To address this, the most useful software products are those able to reschedule dynamically.
A further advance, to ensure maintenance is integrated with production scheduling, is to link scheduling with maintenance work orders and the CMMS. This automates provision of updates on machine availability and downtime, so enabling more timely rescheduling.
In addition, most systems now provide some form of scheduling dashboard. This provides more visibility into production, letting production planners and operators see the order status and priority, along with information on resource utilization and availability.
Production scheduling vs. production planning
ERP systems usually incorporate both functions, which prompts questions about the differences.
Production scheduling is concerned with moving specific orders through the factory and has a focus on the present. It assigns tasks, sets sequences and establishes timelines.
Production planning takes a higher-level, longer-term look at how customer orders will be satisfied. Using demand forecasting, it seeks to ensure the factory will be able to handle the business expected in the future.
The two modules work together, with scheduling executing the production plan. Both rely on accurate data and cross-functional coordination.
Real-world applications in industrial manufacturing
Industrial manufacturers typically take a layered approach to production scheduling. Combining technology with human expertise, they seek to release orders into the factory in a way that optimizes achievement of business goals.
The technology aspect entails MES and ERP integration with the CMMS and any SCADA platforms deployed. This maximizes data availability and accuracy, which are essential in generating realistic schedules.
Within different industries the priorities and points of emphasis vary.
Job shops have complex scheduling challenges, and those in batch manufacturing are not far behind. Discrete manufacturing, where product flows through lines, is less complex but still challenging to schedule, while process operations can be more straightforward.
Many businesses, like automotive component manufacturers, are focused on achieving on-time delivery, while others prioritize inventory control and cost management. Job shops in particular value bottleneck analysis capabilities, as this affects both resource utilization and lead times.
Scheduling in process industries has a different emphasis to that taken in batch production. They take a recipe and batch approach, rather than using discrete units, focus on process optimization, and have constraints like fixed limits on WIP storage capacity (a result of tank or holding vessel size). Those in food and beverage production and pharmaceuticals also have numerous regulatory compliance requirements to incorporate.
Smart scheduling as a competitive advantage
The ability to adapt to changes, whether in external factors like customer demand, or internal constraints and limitations like labor and machine availability, is essential in business today. The faster a business responds, the better it can maximize resource utilization.
Measured by metrics like OEE, utilization is critical for maximizing output and productivity from manufacturing operations. Businesses implement Lean and Agile manufacturing and strive to maximize responsiveness, but these efforts have limited impact without effective and efficient production scheduling.
A sometimes overlooked aspect of scheduling is how Quality Management and Maintenance are integrated into daily operations.
Quality management is essential for minimizing waste and achieving predictable output. Unplanned stoppages are addressed by implementing real-time machine condition monitoring and predictive maintenance. (For more information on these, refer to our “Maintenance Scheduling Guide” and “How to Use AI for Maintenance Scheduling”.)
In a world where on-time delivery is mandatory and resources are finite, the only way to optimize complex manufacturing operations is through dynamic production scheduling. That’s where real competitive advantage exists.
