Manufacturing Process Planning: What, Why & How

Manufacturing Process Planning (MPP) is the process of developing a detailed plan and methodology for the production of your product. It helps your organization make the production process as efficient as possible.

Production Planners all over the world are handling new Industry 4.0 Technologies and the increasing challenges associated with learning new tasks, new hi-tech tools, new volumes of data and faster processes, in order to make a more intelligent predictive analysis of the manufacturing process.

These new procedures can be met with resistance, dependent on the motivation, technology familiarity and agility of the Process Planner.

Industry 4.0 Technologies bring new environments of automation, cyber-physical systems, communications and visibility/monitoring with data processed online using cloud computing. Machine-to-machine communication is required more and more, as the human necessity is removed.

Could MPP be completely automated?

A chance to Automate?

What are the demands for automation and can the knowledge of the human process planner be transferred?

The decision making for primary process selection, operational sequencing and scheduling should be automated and the knowledge of it should be imported in a system that could plan the process and do the scheduling based on CAD and CAM models of the future products, even down to the levels of direct connections to a new batch-of-one, personalized customer product.

This is the new role and environment of a process planner in the 4th Industrial Revolution (4IR).

But first for this to happen, let’s get back to the basics….

What is manufacturing process planning?

MPP is a predetermined process that plans, manages and controls the allocation of human resource, raw material, and machinery to achieve maximum efficiencies.

It provides customers a single, scalable and secure source of manufacturing data that supports lifecycle processes from the latter stages of engineering (incl CAD/CAM) through production.

The single source of knowledge for:

  • products
  • processes
  • resources
  • plants

You can increase manufacturing’s influence on product innovation to drastically improve profitability, time-to-market and quality.

MPP is a sequence of steps that empower manufacturers to work smarter and optimize their production process in the best possible manner. This helps manufacturers work smarter by efficiently managing internal resources to meet customer demand.

Objectives of MPP

Having a reliable MPP software in your company makes it easy to:

  • Ensure a cost-efficient production process
  • Promote the timely delivery of goods
  • Minimize production time
  • Improve customer satisfaction
  • Coordinate with departments about production, to ensure everyone is aligned
  • Ensure the right individual/team is assigned the right work

MPP is at the core of any manufacturing unit. It includes:

  • material forecasting
  • master production scheduling
  • long term planning
  • demand management
  • & more….

The MPP process kicks off with demand forecasting of a product, and thereafter designing the production plan according to the demand to move it forward.

MPP is a strategy to plan a chain of operations that supports manufacturers to be at the right place, at the right time so that they can achieve the maximum efficiency from their resources.

Leading manufacturers are looking for technologies and methodologies that allow them to efficiently author, simulate and manage manufacturing information throughout their organization and with external suppliers. Manufacturers want software tools that can align manufacturing plans quickly and intelligently based on ever-changing product configurations.

The MPP allows design and manufacturing engineers to concurrently develop product and manufacturing process definitions. This ensures that manufacturing constraints are reconciled during product design and vice versa.

MPP Software Solution


Planners define additional relevant manufactured parts issued from assembly or fabrication processes in the design & engineering collaborative environment. They can intuitively reorganize the manufacturing stages of the MBOM using simple drag- and-drop functions and add consumables needed for the manufacturing process from a catalog.


Users of MPP can automatically generate the initial MBOM based on the definition of the product structure or engineering bill of materials (EBOM) from the product designer. They can then make modifications to the plan by simply dragging and dropping parts or entire stage nodes from one step in the plan to another. When product designers modify the product structure, the change can be automatically inserted into the manufacturing stages.


The planner in the central office defines the MBOM, the MAKE or BUY decision for the MBOM node, and the manufacturing plant responsibility. From this MBOM, each planner at a given plant can adapt the MBOM to his local constraint (by adding an assembly stage, for example) and then define his plant-specific MBOM.


  • Plant-specific MBOM definition from a central MBOM
  • Create manufacturing stage templates and save them in catalogs for reuse
  • Support collaborative and concurrent planning for multiple users
  • Update manufacturing definitions anytime to reflect engineering definition changes
  • Easy-to-use user interface for defining manufactured product stages
  • Define and manage the process structure and manufacturing system
  • Perform time analysis based on industry standards
  • Validate operation sequences in 3D
  • One-click view of scope of work
  • Use process plan and manufacturing system templates to capture IP

4IR/Smarter MPP

Traditional MPP is often based at its core on just the knowledge and experience of a team of co-workers. While experienced over many years, now a new 4IR environment is upon us – new customer demands, new technologies to enhance and speed up the Manufacturing process.

Theirs and their team’s experience can often bring a reluctance to change and adapt to this new environment.

As has proven itself over many years, if you fight Technology, you will lose!

Those organizations with a low-tech approach will be left behind and unable to adapt to the drive for smarter, better, more personalized products, delivered faster.

Factory integration leads the charge – manufacturing resources are being connected to data and information exchange with constant quality and process control.

Scheduling of the product manufacturing and supply chain is being resolved through dynamic scheduling.

The following elements should be considered in developing a smart MPP solution:

  • Objectives: determine your objectives and priorities in fitting with the planning environment variables.
  • Requirements specification: validate the operations’ challenges and identify measurables.
  • Analytics & Algorithms: Locate data sources and select relevant analytics and machine learning algorithms to fit those challenges.
  • System Architecture: Design systems and data architecture with a major consideration given to integration with your existing systems landscape and IIoT telemetry.
  • Think scalability & sustainability: Implement with considerations for development methodologies, continuous innovation and long-term scalability.

To explore Smart MPP further, you might want to read my article: The “Waze/GPS” of Manufacturing

Back to Automation

Manufacturing process automation is here today and will only continue to improve each day as the technology becomes more accessible.

An automated manufacturing system isn’t only limited to production lines. It can be a tool that can automate your inventory, orders, purchasing, or even marketing. Pretty much anything can be automated to improve your manufacturing productions.

What is Automation in Manufacturing?

Automation in manufacturing is the process of using MPP Software and Industry 4.0 Technologies, as discussed above and more specifically robotic tools to fully operate a factory when making a physical product.

These tools are built to perform operations to help businesses with tasks such as processing, assembly, inspection, inventory management, and production planning.

In the past, a tool would perform a specialized task, but with technological advancements, the number of operations that a tool can perform has increased. In a nutshell, this is what is meant by process automation.

It’s quickly becoming (think COVID-19 shutdowns) essential to consider full automation of the manufacturing process as we’re already seeing at least 75% of manufacturers using a large amount of automation to improve factory productivity as a key difference in increasing growth.

The Digital Twin is a Core Component for 4IR/Smart MPP

Back to MPP and its core enabler – The Digital Twin. It’s, of course a digital replica of the processes, equipment, people, and devices that make up the factory and can be used for both system design, operations simulation and therefore MPP.

The resources in the system not only have a busy, idle, and off-shift state, but they are objects that have behaviors and can move around the system and interact with the other objects in the model to replicate the behavior and detailed constraints of the real factory.

The Digital Twin brings a new level of fidelity to scheduling that is not available in the existing resource-based modeling tools.

Digital Manufacturing (process) Twin

The Digital Manufacturing Twin is an object-based, data driven, 3D animated model of the factory that is connected to real time data from the PLM, ERP, MES, and related data sources.

System Design and Operation

While out focus is on enhancing throughput and on-time delivery through better scheduling using an existing factory design, unlike traditional scheduling tools, a Digital Manufacturing Twin also optimizes the factory deign.

The same model, used for factory scheduling can be used to test your changes to the facility such as adding new equipment, changing staffing levels, consolidating production steps, adding contingency inventory, etc…

Executable Schedules

A basic requirement of any scheduling solution is that it provides executable schedules that can be implemented in the factory.  If an inappropriate production schedule is sent to the factory floor, the production staff have no choice but to ignore the schedule and make their own decisions based on their isolated information.

For a schedule to be executable, it must capture all the detailed constraints of the system. Since the foundation of the Digital Manufacturing Twin is an object-based modeling tool, the factory model can capture all these constraints in as much detail as necessary. This includes complex constraints such as material handling devices, complex equipment, workers with different skill sets, and complex sequencing requirements.

In many systems there are operating rules that have been developed over time to control the production processes. These operating rules are just as important to capture as the key system constraints; any schedule that ignores these operating rules is non-executable. The modeling framework has flexible rule-based decision logic for implementing these operating rules. The result is an actionable schedule that respects both the physical constraints of the system as well as the standard operating rules.

Fast Execution

In most organizations, the useful life of a schedule is short because unplanned events and variation occur that make the current schedule invalid.  When this occurs, a new schedule must be regenerated and distributed as immediately as possible, to keep the production running smoothly. A manual or optimization-based approach to schedule regeneration that takes hours to complete is impractical, resulting in misaligned KPIs.

When random events occur, the Digital Manufacturing Twin can quickly respond and generate and distribute a new actionable schedule. Schedule regeneration can either be manually triggered by the scheduler, or automatically triggered by events in the system.

3D Animated Model and Schedule

In other scheduling systems the only graphical view of the model and schedule is the resource Gantt chart. In contrast, the Digital Manufacturing Twin provides a powerful communication and visualization of both the model structure and resulting schedule. Ideally, anyone in the organization – from the shop floor to the top floor – should be able to view and understand the model well enough to validate its structure. A good solution improves not only the ability to generate an actionable schedule, but to visualize it and explain it across all levels of the organization.

The associated Gantt chart has a direct link to the 3D animated facility with drill-down capabilities. From that point you can simulate forward in time and watch the schedule unfold as it will in the real the system.

Risk Analysis

One of the key shortcomings of scheduling tools is their inability to deal with unplanned events and variation.  In contrast, the Digital Manufacturing Twin can accurately model these unplanned events and variations to not only provide a detailed schedule, but also analyze the risk associated with the schedule.

When generating a schedule:

  1. the random events/variations are automatically disabled to generate a deterministic schedule. Like other deterministic schedules it is optimistic in terms of on time completions.
  2. However, once this schedule is generated, the same model is executed multiple times with the events/variation enabled, to generate a random sampling of multiple schedules based on the uncertainty in the system.
  3. The set of randomly generated schedules is then used to derive risk measures – such as the likelihood that each order will ship on time. These risk measures are directly displayed on the Gantt Gannt chart and in related reports.
  4. This let’s the scheduler know in advance which orders are risky and take action to make sure important orders have a high likelihood of shipping on time.

Constraint Analysis 

It’s not uncommon that the supply chain planning process which is based on a rough-cut capacity model of the factory sends more work to a production facility than can be easily produced given the true capacity and operational constraints of the facility.  When this occurs, the resulting detailed schedule will have one or more late jobs and/or jobs with high risk of being late.  The question then arises as to what actions can be taken by the scheduler to ensure that the important jobs all delivered on schedule.

Although other scheduling approaches generate a schedule, the Digital Manufacturing Twin goes one step further by also providing a constraint analysis detailing all the non-value added time that is spent by each job in the system. This includes time waiting for a machine, an operator, material, a material handling device, or any other constraint that is impeding the production of the item.

As a result, if the schedule shows that an item is going to be late, the constraint analysis shows what actions might be taken to reduce the non-value added time and ship the product on time.

Localized Models

In global applications there are typically multiple production facilities located around the world that produce the same products. Although each facility has its own unique layout there is typically significant overlap in terms of resources (equipment, workers, etc.) and processes.  In this case your Digital Manufacturing Twin needs to provide special features to allow the Digital Twin for each facility to be automatically generated from data tables that map to modeling components that describe the resources and processes.  This greatly simplifies the development of multiple Twins across the enterprise and also supports the reconfiguring of each Twin via data table edits to accommodate ongoing changes in resources and/or processes.

Having the Manufacturing Process Planning process fully automated can soon become a reality. Manufacturers need only be careful to consider all aspects of implementation, and not rush it.

The Automated Manufacturing Production Plan, c/o The Digital Manufacturing Twin will soon by your de facto for Manufacturing.