The Simulation Series, Part I:
Navigating Complex Manufacturing Systems Using Simulation

Male engineer in high visibility vest using laptop computer looking at automotive manufacturing facility

Simulation can improve productivity, reduce time-to-market, lower production costs, and increase market share and profitability.

Welcome! In this series we'll explore the powerful role that simulation plays in revolutionizing manufacturing processes. Join us as we uncover the key concepts, applications, and benefits of simulation technology in optimizing efficiency and driving innovation in the manufacturing industry.

In Part I, we begin with an overview of manufacturing systems and the benefits of using simulation in manufacturing.

As the series unfolds, we'll also cover Manufacturing Simulation Types, Discrete Event Simulation, Robotics Simulation, and Emulation.

The Manufacturing System: It Must Be Connected and Flexible

The manufacturing industry is under constant pressure to produce and deliver innovative products on shorter timelines. Staying competitive requires manufacturing systems to be connected and flexible. All nodes in the production process and across the product life cycle matrix must seamlessly collaborate and exchange information in real-time. These requirements, however, add complexity to an already complex environment, one where markets continue to trend toward globalisation and decentralisation of manufacturing.

The Manufacturing System: Why It's Complex

The manufacturing system is a complex entity comprised of various overlapping and interactive internal and external elements. It receives inputs such as orders, raw materials, components, and energy from the outside world and then uses a set of resources and procedures to transform those inputs into the products desired by customers.

Likes other institutions, the manufacturing system is limited — internally and externally — by physical, financial, human, and political constraints.

While functionality is the core of a manufacturing system’s operation, its activities must overlap and interact with other internal functions. Process engineering, product engineering, applied science and technology, administration, management, procurement, marketing, sales, and service are among them. Those internal functionalities then overlap and interact with external functionalities, such as customers, vendors, suppliers, communities, and governments. In combination, internal and external factors make the manufacturing system very complex.

Simulation: A Solution for Navigating the Complexity of Manufacturing Systems

Research and development in computer science and computation is driving societies closer to adopting simulation in more aspects of daily life, including business.

Industries can already use simulation to effectively manage their manufacturing systems by virtually simulating the various overlapping and interacting activities that make them complex.

Specifically, simulation modelling and analysis allows manufacturers to develop and test new concepts, systems, operating policies, and resource policies before implementation, thus speeding up implementation while at the same time reducing the risk of failure and downtime. Simulation also helps to gather information and knowledge without disturbing the actual system.

Simulation modelling and analysis can help manufacturing industries in many ways: from designing, enhancing and optimising the manufacturing systems, to improving productivity, reducing a product’s time-to-market, lowering production costs and increasing market share and profitability. How? Because simulation allows a system-wide view of the effect of local changes to the manufacturing system. If a change is made at a particular station, its impact on the performance of this station may be predictable. On the other hand, it may be difficult, if not impossible, to determine ahead of time the impact of this change on the performance of the overall system.

The Benefits of Simulating a Manufacturing System

There are numerous potential benefits of simulating a manufacturing system, including:

  • Increased throughput
  • Decreased times in system of parts
  • Reduced in-process inventories of parts
  • Increased utilizations of machines, MHE and workers
  • Increased on-time deliveries of products to customers
  • Reduced capital requirements or operating expenses
  • Insurance that a proposed system design will operate as expected

In addition to validating all contributing factors of greenfield projects at early stage, simulation can also be used to identify inefficiencies in brownfields and analyse how new equipment, materials, and other changes can impact those projects, too.

Furthermore, manufacturing simulation can be used for line balancing, capacity planning, programming robotics, and automating equipment at the early stage of projects. It can also be used when change demands, such as product mix, occur. All told, simulation modelling and analysis can overcome myriad manufacturing issues, which could be classified into three general categories:

  • The need for and the quantity of equipment and personnel
    • Facility layout and resource allocation
    • Requirements for material-handling systems and other support equipment
    • Requirements of storage systems such as ASRS, replenishment rates, batch sizes, etc.
    • Evaluation of a change in product volume or mix
    • Evaluation of the effect of a new piece of equipment such as robot on an existing manufacturing line
    • Evaluation of capital investments
    • Labor-requirements planning
    • Number of shifts
  • Performance evaluation
    • Throughput analysis
    • Capacity utilization analysis
    • Time-in-system analysis
    • Lead time analysis
    • Inventory turns analysis
    • Schedule attainment
    • Bottleneck analysis i.e. determining the location of the constraining resources
  • Evaluation of operational procedures
    • Production scheduling
    • Policies for component-part or raw-material inventory levels
    • Control strategies of MHE such as AGV and conveyors
    • System reliability analysis such as effect of preventive maintenance
    • System availability predictions and analysis
    • Overall equipment effectiveness analysis
    • Quality-control policies such as Six Sigma
    • Just-in-time (JIT) strategies
    • Just-in-sequence flow

That concludes Part I of Navigating the Complexity of Manufacturing Systems Using Simulation. In Part II, we'll explore the different types of manufacturing simulation.

In the meantime, to find out how Actalent can help your business manage its manufacturing system using simulation, contact us.


Manufacturing Systems: Foundations of World-Class Practice (1992), National Academy of Engineering
Practical Reliability Engineering, John Wiley & Sons Ltd.
Development of Integrated Manufacturing Systems, O'Sullivan D.