Simulation technology is being increasingly seen as improving quality in manufacturing
In the current highly competitive environment, the manufacturing industry is facing constant challenges of producing innovative products at shortened time-to-market. With the increased pull toward product personalization and mass customization, companies are looking for capabilities that help their concepts turn into goods reliably, economically, and quickly.
Products are becoming more complex by the day, driving companies to increase technology at every stage of the product development and manufacturing process. However, when most people think of advanced manufacturing technologies, the first that comes to mind are usually factory automation, and the use of robotics in manufacturing. While they are important, one technology that also plays a valuable role in the new era of manufacturing is simulation.
A recent survey by Onshape showed that 75 percent of manufacturing executives believe simulation is critical for success. This shift is driving tremendous growth in the market, the global simulation software market size was estimated at $13.25 billion in 2021, and is expected to reach a revenue of $39.74 billion in 2030.
Manufacturing simulation focuses on modeling the behavior of manufacturing organizations, processes, and systems. Organizations, processes, and systems include supply chains, as well as people, machines, tools, and information systems. For example, manufacturing simulation can be used to evaluate the manufacturability of new product designs, support the development and validation of process data for new products, assist in the engineering of new production systems and processes, and ultimately evaluate their impact on overall business performance. On the manufacturing floor, it can also be used to model “as-is” and “to-be” manufacturing and support operations from the supply chain level down to the shop floor.
The importance of simulation in manufacturing mainly lies in the fact that manufacturing systems, processes, and data are growing ever more complex. Product design, manufacturing engineering, and production management decisions often involve the consideration of many interdependent variables. These decisions often have a long-term impact on the success or failure of the manufacturing organization. It is extremely risky to make these major decisions based on gut instinct alone. Simulation provides a capability to rapidly conduct experiments to predict and evaluate the results of alternative manufacturing decisions. It has often been said that you do not understand your industrial processes and systems until you try to simulate them.
Simulation models, while initially seen as a design tool, are now built to support decisions regarding investment in new technology, expansion of production capabilities, modeling of supplier relationships, materials management, human resources, etc. They are built to support a product lifecycle. The adoption of numerical simulation at an early stage leads to optimized designs and reduces the number of physical prototypes, all of which point toward a shorter time to market. A high-fidelity simulation can reflect reality closely and serve as an accurate predictor of a design’s performance by including all of the physical phenomena involved and being able to describe the interactions as they happen in the real world. The level of accuracy delivered by a multi-physical analysis has become the norm for many companies.
The increasing trend towards globalization requires real-time information exchanges between the various stages in a product development life cycle, e.g., design, setup planning, production scheduling, machining, assembly, etc., as well as seamless collaboration among these stages. Simulation modeling and analysis is conducted to gain insight into this kind of complex system, to achieve the development and testing of new operating or resource policies and new concepts or systems, which live up to the expectation of modern manufacturing, before implementing them and to gather information and knowledge without disturbing the actual system.
The biggest factor for the growing spread of simulation is simply put, the reduction in investment risk. Simulation solutions in an industry help the manufacturer to gain a better insight into what their operation needs. This insight would not only help the manufacturers to save time but also use the right resources at the right time. Simulation results in the overall improvement in the quality of products as well as processes. The key advantages of simulation in the manufacturing industry include waste minimization, efficiency improvement, reduction in energy consumption and optimization of resources, and early detection of risks to protect human lives.
There are a few factors currently inhibiting the use of manufacturing simulation, the top two are discussed here. The monetary investment would be the primary factor, however, it is important to note that these costs must be weighed against the risks of not using simulation technology. There are countless case studies where companies have either realized significant cost savings or avoided major disasters through the effective use of simulation. Undoubtedly, if complex manufacturing systems are involved, simulation is probably the only reliable mechanism for predicting and evaluating the performance of the system under varying loads and operating conditions. Another challenge is transferring data between simulation and other manufacturing software applications. Currently, the environments are distributed computing environments where other non-simulation manufacturing software applications are running and interacting with one or more simulation systems, sometimes in geographically dispersed locations. Multiple simulation software processes that are independently executing and interact with each other, and their ability to transfer data seamlessly plays a key role in the effectiveness of simulation on a large scale.
Today, manufacturers can leverage simulation technology to make products that require less material and are more cost-effective to make than ever before. Designing and manufacturing simulation can take into account factors like reductions in the energy needed to manufacture a product, or the material needed to make up a part or a system of parts, and what emerges are sometimes interesting shapes that reduce costs and take a lighter toll on the environment. By saving energy, raw materials, and money, the process has the potential to transform the way things are manufactured. It is happening now in select companies large and small, from global conglomerates to social enterprises.
Shirin Hameed, Chief Marketing Officer (CMO) at Detroit Engineered Products (DEP), has over 13 years of experience with a proven track record of accomplishment in planning and leading comprehensive marketing projects in the B2B technology space.