Digital Manufacturing

The following is my summary of the areas within the whole digital manufacturing space which is complemented by using the digital twin workflows and concepts to provide Leaner manufacturing solutions.

Many key Blue-chip organisation strive for lean cost effect processes across individual processes applying ‘KAIZEN’ to improve business operations continuously, driving for innovation and evolution and effectively for High Quality, Lowest Cost and the Shortest Lead times. Typically, these processes improvements are focused on troubled areas and isolated from other key link processes. To look at Lean Manufacturing we need to include digital design and manufacturing (or simply “digital manufacturing”) as the aggregation, analysis, and application of data across the lifecycle of a manufactured product and into the service and maintenance of the product and to include data of both product and process data from across the value chain.

?The goal for manufacturers is to demonstrate and apply digital manufacturing technologies, to accelerate these technologies to market, and to increase the competitiveness of manufacturing and service-based businesses. This also combines the integration of information systems across the product lifecycle, digital links between design and fabrication, and smart manufacturing practices within the factory and supply chain, plus the inclusion the integration of smart sensors and controls with manufacturing equipment, as well as machine intelligence at the level of the equipment and the cell. Advanced Analysis includes data analysis, algorithms, and computing technologies.

?Systems Design in the Digital Thread

Currently, tools and methods used in the design of products and systems have very limited, or no capacity, to support real-time automated, or semi-automated, guidance for decision making in light of life cycle considerations, or “utilities” such as producibility, serviceability, usability, sustainability, and more. Early design for utilities” guidance would enable more producible, serviceable, usable, sustainable, safe, and customer valued lower-cost designs and shorter product development cycles with fewer design iterations.

Whether embodied in intelligent systems or more human guided, solutions are needed that enable and integrate the wide array of stakeholders across the eco-system in the design of products and systems (e.g., suppliers, OEMs, ODMs, end users).

Smart Factory Visibility and Real-Time Optimisation

The visualization of real-time data within a factory, and the use of this data for real-time optimisation of factory efficiency, robustness, and profitability hold great promise for bringing about a significant reduction in the design-build cycle. The digital integration of the manufacturing enterprise will feature the seamless flow of data between different stages of the product lifecycle, and between different parts of the value chain. This data can be analysed to improve factory operations and shared within a value chain to benefit others. It is desirable to aggregate and analyse process data within a factory in order to make real-time decisions that improve factory operations, and to make this critical data available to factory operators and to other parts of the value chain. Real-time optimisation of factory operations will result in improved asset utilisation, higher product quality, and more efficient use of energy, labour, and materials. Visibility of these factory operations by others will result in increased supply chain efficiency, more effective procurement, and faster time to market.

?End to End Supply Network Synchronisation

The success of a modern company greatly depends on the ability to collect and use data to plan and manage the manufacture and distribution of its products. Supply network optimisation is difficult given today’s globally distributed businesses and marketplace, where businesses experience increased variability in market demand, increased complexity in transportation, and distributed manufacturing. Hence, it is important to define and implement a more efficient equilibrium between demand, production capacity and agility and inventory management. It is important to include suppliers in the need for defining and implementing a more efficient equilibrium. The use of technology to support supply chain analytics and supply chain visibility are key to network synchronisation and optimisation.

?Full System Integration of the Digital Fabric

Product information often does not flow smoothly through manufacturing processes, between organisations or across the life cycle of manufactured products. This discontinuity can arise for many reasons; gaps in technological integration or capability, organisational structure, individual or team incentives, and combinations of each. Limited ability for information sharing and extraction across different disciplines and needs causes substantial wastes in terms of time, materials, and labour. These limitations also affect the quality and performance of products. Data, information, and knowledge can be found in a variety of formats in an organization and include quantitative and qualitative measures, making the flow and integration even more challenging. Moreover, true integration requires orchestrating and connecting sources within and between organizations that are in varying formats, purposes, and distributed widely.

?Completing the Model-Based Definition

Current industrial implementations of model-based definition (MBD) primarily deal with shape capture of a product. Moreover, it is inherently dependent upon the software system that authors the model, which is most often a commercial CAD software. In order to enable additional consumers of information among the stakeholders in the life cycle, the model-based definition must address not only shape, but behaviour and context as well. It must also be able to be dynamically scaled with respect to level of detail regarding shape, behaviour and context to enable and promote consumption throughout the life cycle. For example, in addition to shape, behaviour and context, product manufacturing information (PMI) should be accommodated. MBD should also include process data and as-built variability during the manufacturing life cycle. This has the potential to reduce cost, increase quality, and enable better (and more accurate) communication within the supply chain and sustainment efforts. Model-based definition is fundamental to the digital thread; a critical communication conduit for the product life cycle.

?Closing the Gap in SME Engagement in Digital Manufacturing

Large OEMs with the resources available are often sophisticated users of digital manufacturing technologies, while small and medium-sized enterprises (SME's) with fewer resources are not. This capability gap creates significant inefficiencies along the value chain, where the size, scope and challenges of SME's can be quite varied. Significant problems can result when large companies use digital manufacturing technologies and small to medium size companies do not. Benefits from technologies for data sharing, life-cycle data availability, and supply chain analytics, to name a few, are severely limited without participation of the full value chain. Ultimately, the goal is to enable all of the organisations within a value chain to use digital manufacturing technologies for the design and production of new products. Solving this problem would result in greater innovation, quality and value to customers, at reduced costs and speed the time to market.

?Communication Standards for Intelligent Machines

The realization of digital manufacturing critically hinges on the ability to securely and easily capture, transfer, and analyse data from production machine tools. This requires multi-functional, simply discoverable, and affordable sensing technologies that can be easily integrated into both new and legacy systems, and that possess plug-and-play functional characteristics. While many modern machine tools possess sensing and control systems, the data communications and digital interfaces are frequently complex and/or proprietary. The lack of plug-and-play type digital integration is an obstacle to achieving seamless digital operation of these machines within the manufacturing enterprise.

?Cyber Security of Intelligent Machines

In spite of the ever-increasing use of computers and data exchanges between machines and operators on the shop floor there is a marked absence of adequate cyber security measures and technologies for the prevention of potentially catastrophic security breaches. Shop floor level security has been enforced in many cases by completely restricting any network capability of the equipment. Such restrictions prohibit the adoption of digital manufacturing technologies. The realization of the envisioned digital tapestry that requires real-time connectivity, communications and data exchanges from the lowest machine to the highest enterprise-levels necessitates the development of structured and standardised security measures and protocols.

?Operating System for Cyber Physical Manufacturing

Most factories consist of multiple machine tools, robots, and inspection tools that originate from various vendors. The dynamic organization, and reorganization, of these resources can be costly and slow. The challenge is particularly acute for small businesses, which often do not have access to software tools such as MES and MRP.

An Operating System for Cyber Physical Manufacturing (OSCM) will make it possible to efficiently and dynamically organize and integrate heterogeneous manufacturing hardware resources. The OSCM will result in an accessible and standardised manufacturing capacity to allow manufacturing enterprises to streamline and dynamically control and configure their internal resources and external supply networks.

Intelligent Machining Toolkit

A key limitation of conventional machine tools is their lack of intelligence. In general, manufacturing equipment is not self-monitoring, error-correcting, or capable of adapting to variations without custom developed application-specific algorithms. The development and maintenance of such intelligent systems is expensive and often requires technical expertise that is not widely available. There is a need for commercially available intelligent machine tool solutions that are low cost, scalable, and capable of plug-and play type interoperability.

?Agile Manufacturing to Compensate for Production Variability

Agile Manufacturing is defined to be the tools, processes, and training to be able to respond quickly to market changes. The typical output of Agile Manufacturing is to quickly deliver new products to respond to these market changes. It is desirable to extend Agile Manufacturing processes to respond to variability in a product rather than market changes. Production variability exists for all manufactured components in a product regardless of manufacturing process or processing order. The cost of variability is typically quantified in terms of part yield, where nonconforming components are reworked or scrapped which is a short sighted perspective because the variation in the performance of the assembled system requires more intensive maintenance, shorter maintenance cycles, designed-in margins and tighter tolerances, all of which contribute more to the lifecycle cost of a system than costs associated with low component process yields. Performance prediction should focus on the lifecycle costs of the entire product.

?Shop Floor Augmented Reality and Wearable Computing

Shop floor technicians and assembly operators spend significant amounts of time looking for work instructions, recording information, and attempting to share information with others. Many tasks performed by shop floor technicians could be significantly accelerated by capturing what the technician is doing, and by delivering dynamic work instructions based on those actions. The largest opportunities for productivity improvements involve complex, non-routine tasks including machine maintenance and product re-work, as well as training and re-training on the shop floor. Natural, convenient, and relevant information provided to the technician could lead to higher resource utilisation, operational effectiveness, and product quality.

?Virtually Guided Certification

The cost and time to certify a manufacturing process, material, and design can be significant. Depending on the application, current estimates place the insertion of a single materials system into a complex design at tens of millions of ￡/$ (or more) and 15 years. This time and cost is not acceptable in a competitive worldwide market. Any change in a certified process can almost be impossible to make, even if the improvement is large, due to the time and cost of certification.?