Flexible Manufacturing Systems Combined with Industry 4.0 Can Further Progress Toward Mass Customization

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While in the past, manufacturing costs were driven by mass production – producing the same high-quality products at volume at high speed – today’s costs are driven by mass customization – the ability to produce a wide variety of products to meet expanding market demand at volume at high speed. Mass customization is the holy grail of modern manufacturing, as it requires companies to apply a higher level of automation and machine intelligence, also increasing costs and often slowing the production process. Flexible manufacturing systems (FMS), which automate machine processes, were designed to solve these problems. To achieve this goal, companies are increasingly combining FMS with Industry 4.0 technology.

Flexible manufacturing systems place in Industry 4.0

FMS focus on automating machine cells operating as a system, consisting of processing workstations, automated material handling, and material storage. FMS use computer controls to enable machines to identify and distinguish among different part styles processed, perform quick changeovers of operating instructions, and perform physical machine setup. FMS consist of two categories: machine flexibility and routing flexibility. Machine flexibility engages various types of computer numerical control (CNC) machines to provide automated controls of dozens of types of machining tools, such as drills, boring tools, and lathes. A CNC machine processes a piece of material (metal, plastic, wood, ceramic, or composite) to meet specifications by following a coded programmed instruction without a manual operator. Routing flexibility refers to the movement of materials, parts, and in-process goods from one machine to the next for each stage in production.

In recent years, CNCs have been further optimized with additional levels of automation, such as the use of robots and cobots for machine process steps and routing. Advances in computer-aided design (CAD) are also playing a role in enhanced FMS capability. For example, the part to be machined has mechanical dimensions that are defined using CAD software and then translated into manufacturing directives. In addition, the ability to apply artificial intelligence to the design phase through techniques like generative design can improve the manufacturability of the end product and parts, making it feasible to optimize the production process.

Next steps for FMS

FMS are only the beginning of the path to mass customization. In FMS, each machine can be made as flexible as possible through tool selection and adaptable computer controls, but once they are in place, there is still a limited number of functions they can perform. In the end, FMS are complicated systems that require high initial setup costs and employ a combination of skilled workers and expensive robotics to tune to a given set of process parameters. Once in place, manufacturers are loath to incur additional expenses to make major changes. This results in greater flexibility but still limits production to a defined set of parameters. Digital transformation can improve this picture. For example, artificial intelligence can be employed to enhance machine decision-making models.

A good example of FMS and digital technologies working together is Siemens Electronic Works in Amberg, Germany. The 108,000 ft2 plant includes computer-controlled machines collaborating with 1,100 employees that produce the company’s Simatic control devices, comprising more than 50,000 annual product variations across 950 different products. Quality control measures have shown that the plant records only 15 defects per million parts and maintains a 99% reliability rate. To accomplish this, Siemens has overlaid a digital product life cycle management system, which monitors and optimizes the change process across the product lines, over CNC industrial machines, which communicate using an IIoT platform connected to manufacturing execution systems. Siemens has also transferred the lessons learned in Amberg to its Electronic Works in Chengdu, China.

For all their automation, though, these plants still offer a select amount of customization across a single product line. To transform production further, new approaches to materials may be required. 3D printing represents one example of such a transformation. With digital design and production of the parts and end product combined in many cases, 3D printing demonstrates true flexibility. However, the technology costs about 10 times per unit more than traditional processes, causing it to be used for small lots rather than large-scale production.

Facing these challenges, manufacturing companies should not stop at FMS. Manufacturers should enhance FMS with digital transformation technologies like AI, generative design, and 3D printing (where applicable). Lessons from early adopters include increasing automation through adding a digital management layer (such as product life cycle management) to existing FMS or introducing new techniques to translate design parameters to manufacturing directives. Clients should take these lessons from these emerging areas to continue the journey toward mass customization.

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