About IFS.ai Manufacturing Scheduling and Optimization (MSO)

IFS.ai Manufacturing Scheduling and Optimization (MSO) is a finite scheduling solution using intelligent optimization algorithms to create feasible and optimized production schedules in constraint-based manufacturing environments. Rather than relying on traditional rule-based scheduling methods, MSO creates finite production schedules based on overall optimization of a scheduling score. It considers availability in critical finite resources, and ensure those are not overloaded.

Instead of creating production schedules manually, a process that can be time-consuming and may lead to inefficient resource utilization or missed delivery targets, MSO helps planners make better decisions and improve production performance.

MSO relies on high-quality data, clear routines, and a short, execution-oriented planning horizon. It is intended for detailed short-term scheduling. For more long-term planning, other planning mechanisms such as capacity requirements planning, material requirements planning and master scheduling is recommended.

Who This Feature Is For and Why It Matters

This feature is designed for roles involved in short-term production planning and scheduling, including:

• Production planners and inventory part planners who create and evaluate shop order schedules that respect available machines, labor, and tools, ensuring that promised delivery dates stay realistic.
• Production supervisors and machine operators who use the generated schedule to execute shop floor work in the correct sequence.

Use this feature when you need to:

• Create feasible production schedules that respect resource constraints.
• Optimize the utilization of machines, tools, and labor.
• Improve delivery performance and schedule reliability.
• Reduce bottlenecks and production inefficiencies.

By using this feature, you can:

• Generate feasible optimized finite production schedules.
• Improve utilization of critical resources.
• Reduce planning effort and manual schedule adjustments.
• Improve predictability and production flow.
• Support better on-time delivery performance.
• Reduce work-in-progress and inventory levels through improved scheduling decisions.

Where to Find It

Access this feature from the:

• Finite Scheduling Basic Data page
  • Product Area: Manufacturing Scheduling and Optimization (MSO)
  • Location: Full page
• MSO Advanced Parameters page
  • Product Area: Manufacturing Scheduling and Optimization (MSO)
  • Location: Full page
• Smart Manufacturing Planning Board – Resources page
  • Product Area: Manufacturing Scheduling and Optimization (MSO)
  • Location: Full page
• Smart Manufacturing Planning Board – Operations page
  • Product Area: Manufacturing Scheduling and Optimization (MSO)
  • Location: Full page
• Smart Manufacturing Planning Board Filter page
  • Product Area: Manufacturing Scheduling and Optimization (MSO)
  • Location: Full page
• Finite Schedule Shop Order(s) page
  • Product Area: Manufacturing Scheduling and Optimization (MSO)
  • Location: Full page
• Shop Order page
  • Product Area: Manufacturing
  • Location: Finite Schedule command in the command group Scheduling in the command bar at the top of the page
• Shop Orders page
  • Product Area: Manufacturing
  • Location: Finite Schedule command in the command group Scheduling in the command bar at the top of the page
• Operation Block page
  • Product Area: Manufacturing
  • Location: Finite Schedule command in the command bar at the top of the page and the Finite Scheduling Configurations section

How the Feature Uses Data

When finite scheduling is executed, the feature extracts manufacturing scheduling data and turns it into an input load XML file. The file is sent to the scheduling engine, which generates an optimized finite production schedule and returns the result.

It extracts data such as:

• Shop orders (including operations and materials)
• Work centers
• Manufacturing labor classes
• Manufacturing tool groups
• Work calendars
• Material availabilities

 The feature does not use:

• Personal data
• Data not relevant for the scheduling scope

Understanding the Output

This feature schedules shop order operations and updates finite resource assignments.

When reviewing the output, pay particular attention to:

• Operation start and finish times – Verify that operations are scheduled as expected and that planned dates align with delivery commitments.
• Resource assignments – Review which machines, labor resources, and tools have been allocated to each operation.
• Unscheduled operations – Investigate any operations that could not be scheduled, as these often indicate capacity shortages, missing data, or conflicting constraints.
• Resource utilization – Identify underutilized, or bottleneck resources and overloaded infinite resources that may impact throughput.
• The Smart Manufacturing Planning Board - Resources and Smart Manufacturing Planning Board - Operations pages that provide graphical views of the schedules generated by MSO in both resource and operations view. They help planners understand resource load, operation sequencing, bottlenecks, and delivery performance, and enables them to analyze, review, and interact with the production schedules.

Enabling and Using the Feature

This feature is available for customers with access to Manufacturing Scheduling and Optimization. The deployment model can be hybrid/hosted (requires IFS.ai Activation Pass), cloud (requires PSO sizing and purchase of PSO Cloud Service) or remote.

Prerequisites

• Shop orders with operations have been generated and contain valid scheduling data such as machine setup time, machine run time, labor setup time, labor run time and labor crew size.
• High-quality master data is available, as schedule quality depends on the quality of the input data provided to MSO. For example:
  • Work centers, labor classes, and tools have been configured as required.
  • Resource calendars have been generated and accurately reflect actual availability.
  • Routings contain valid scheduling data such as machine setup time, machine run time, labor setup time, labor run time and labor crew size.
• A scheduling optimization configuration is available and connected to an operational scheduling server.

Configuration Requirements

• The site must be configured for MSO scheduling on the Finite Scheduling Basic Data page, with relevant parameters defined. The selected scheduling server configuration must be connected to an operational scheduling server.
• The dataset for the site must be active.

Review and Refine

• Ensure master data of high-quality is available.
• On the Finite Scheduling Basic Data page, verify that:
  • The defined parameters are appropriate. Particular attention should be paid to Mode, Time Horizon (Days), Schedule Acceptance Quality and Generate Schedule within (Min).
  • The selected scheduling server configuration is connected to an operational scheduling server by clicking Check Server Status.

Schedule

When the scheduling mode defined on the Finite Scheduling Basic Data page is Manual, finite scheduling at the site is performed only when a planner explicitly requests it. The following scheduling approaches are possible:

• Full site scheduling: Finite scheduling is executed across all the eligible shop orders at the site. This is initiated from the Finite Schedule Shop Order(s) page by clicking Schedule.
• Subset scheduling: Finite scheduling is executed for a filtered subset of eligible shop orders. This is initiated from the Finite Schedule Shop Order(s) page by first defining the filter criteria to be used and then clicking Schedule.
• Selective scheduling: Finite scheduling is executed for one or several specific shop orders. For example, this is initiated from the Shop Order or Shop Orders page by clicking the Finite Schedule command in the command group Scheduling in the command bar at the top of the page. It can also be triggered from other pages.
• Operation block scheduling: Finite scheduling is executed for operations in an operation block. As result, operations within the block, as well as other operations on affected shop orders, are scheduled. This is initiated from the Operation Block page by clicking the Finite Schedule command in the command bar at the top of the page.
  Note: This is only possible when the site has Include Operation Blocks enabled on the Finite Scheduling Basic Data page.
• Selective optimization on resources: Planners can selectively apply optimization constraints using the Selective Optimization dialog, offering greater control over the scheduling process.

When the scheduling mode is Automatic, finite scheduling is performed automatically whenever required, for example when a new shop order within the selection window is created. Note that this mode is not available with the hybrid/hosted deployment model that requires IFS.ai Activation Pass.

Example Actions

Based on extracted results, you may:

• Review resource utilization to identify bottlenecks, capacity constraints and underutilized resources.
• Analyze tardy or unscheduled shop orders and investigate the constraints or dependencies preventing them from being scheduled as expected. If required, take appropriate action and generate a new schedule.
• Adjust scheduling data or parameters and generate a new schedule. For example, add an additional shift, increase available capacity, or modify scheduling priorities to improve delivery performance.
• Use the Smart Manufacturing Planning Board - Resources and Smart Manufacturing Planning Board - Operations pages to manually adjust the schedule, such as moving an operation to a different resource or time slot to address exceptional planning situations.
• Evaluate the impact of scheduling decisions on delivery performance, resource utilization, production throughput, and overall schedule quality.
• Execute production in accordance with the generated production schedule.

Important to Know

• MSO uses advanced optimization algorithms to generate production schedules. It does not use machine learning models to create or optimize schedules.
• The generated schedule represents the best solution that the scheduling engine can produce based on the available data, business objectives, scheduling constraints and defined parameters.
• Schedule generation time and perceived quality may vary depending on the number of activities being scheduled, the complexity of the manufacturing environment, and the selected optimization settings, such as Schedule Acceptance Quality and Generate Schedule Within (Min).
• Depending on the constraints and available capacity, it may not be possible to schedule all operations or meet all delivery requirements. In such cases, some orders may be tardy and some operations may be unscheduled.
• Schedule quality is directly affected by the quality and completeness of the input data, including routings, operation times, resource definitions, calendars, priorities, and due dates.
• Manual intervention may occasionally be required to address exceptions, unexpected real-world events, or business requirements that cannot be resolved automatically.
• MSO is primarily intended for detailed short-term scheduling. Excessively long planning horizons or large scheduling volumes may negatively affect scheduling performance and schedule quality.
• If the scheduling results are not satisfactory, review the scheduling data, capacities, calendars, resources, and optimization parameters before generating a new schedule.