Digital twin-driven decision support approach of production process for smart manufacturing

The Cambridge Engineering Selector (CES) is a tool that focuses on material, process, and shape combinations of product design. The Resource Consumption Model (RCM) is a tool that focuses on production process resources, resource costs, production volume, production capacity, and manufacturing cycle time. Both tools help identify viable manufacturing process alternatives to meet stated manufacturing objectives.

Highly accelerated life testing has been heavily promoted at Sandia (and elsewhere) as a means to rapidly identify product weaknesses caused by flaws in the product's design or manufacturing process. During product development, a small number of units are forced to fail at high stress. The failed units are then examined to determine the root causes of failure. The identification of the root causes of product failures exposed by highly accelerated life testing can instigate changes to the product's design and/or manufacturing process that result in a product with increased reliability. It is widely viewed that this qualitative use of highly accelerated life testing (often associated with the acronym HALT) can be useful. However, highly accelerated life testing has also been proposed as a quantitative means for "demonstrating" the reliability of a product where unreliability is associated with loss of margin via an identified and dominating failure mechanism. It is assumed that the dominant failure mechanism can be accelerated by changing the level of a stress factor that is assumed to be related to the dominant failure mode. In extreme cases, a minimal number of units (often from a pre-production lot) are subjected to a single highly accelerated stress relative to normal use. If no (or, sufficiently few) units fail at this high stress level, some might claim that a certain level of reliability has been demonstrated (relative to normal use conditions). Underlying this claim are assumptions regarding the level of knowledge associated with the relationship between the stress level and the probability of failure. The primary purpose of this document is to discuss (from a statistical perspective) the efficacy of using accelerated life testing protocols (and, in particular, "highly accelerated" protocols) to make quantitative inferences concerning the performance of a product (e.g., reliability) when in fact there is lack-of-knowledge and uncertainty concerning the assumed relationship between the stress level and performance. In addition, this document contains recommendations for conducting more informative accelerated tests.

With the rapid development of smart manufacturing, some challenges are emerging in the production management, including the utilization of information technology and the elimination of dynamic disturbance. A digital twin-driven production management system (DTPMS) can dynamically simulate and optimize production processes in manufacturing and achieve real-time synchronization, high fidelity, and real-virtual fusion in cyber-physical production. This paper focuses on establishing DTPMS for production life-cycle management. First, we illustrate how to integrate digital twin technology and simulation platforms. Second, a framework of DTPMS is proposed to support a cyber-physical system of production workshop, including product design, product manufacturing, and intelligent service management. Finally, the proposed DTPMS is applied to the production process of a heavy-duty vehicle gearbox. The experimental results indicate that the defective rate of products and the in-process inventory are reduced by 34% and 89%, respectively, while the one-time pass rate of product inspection is increased by 14.2%, which demonstrates the feasibility and effectiveness of the DTPMS.

Quality Function Deployment (QFD) has long been used as a successful design methodology in the heavy industrial and automotive industries. QFD helps designers utilize the ‘voice of the customer’, or customer requirements, to determine which engineering metrics or product specifications are the most essential [1]. This prioritization helps designers know what part of the product or process is most beneficial to focus on during design, resulting in products that better meet customer requirements and generate increased commercial success. QFD and most other design methodologies have rarely been applied to MEMS products [2]. In the case of QFD, the structure of the most common format of the tool dictates that engineering metrics should be related to parts characteristics in the second step of applying QFD. This causes difficulties in using the tool for MEMS as most MEMS do not have physical ‘parts’ that are assembled into a final device. Rather, MEMS have product specifications and a manufacturing process used to create the product. Generally there is a tight link between product and process in MEMS. This link has been utilized in creating a modified version of QFD that relates engineering metrics to design concepts, including product conceptualization and manufacturing process. The modified QFD utilizes aspects of Pugh Concept Selection, and differs from typical QFD primarily in consideration of product idea and manufacturing process in the early phases of product definition. The modified QFD was applied to a MEMS project whose goal was to develop a handheld device that allows users to control the selection and release of a variety of stored scents. The technique was also applied to a microscale heat exchanger for integrated circuits. The scent dispenser and heat exchanger were designed and prototyped at Stanford University in 2005 and 2006, respectively. The modified version of QFD gave insight early in the product definition phase on which design concept to pursue to prototype. Use of this and other design methodologies in the MEMS field could shorten the time it takes to progress through product development to volume manufacturing, and increase confidence in the marketability of the chosen design and manufacturing process. A case study demonstrating the effects of using modified QFD Phase II to assist in finding a good fit between technical capabilities and market application was performed by the author on an acoustic sensor technology [3].

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Nowadays agile and practical methods for lean manufacturing and production process reengineering are in urgent need for Small and Medium Enterprises (SMEs). However, due to the limitations in obtaining accurate performance evaluations of the production line, traditional value stream mapping (VSM) methods are insufficient or unpractical in undertaking production process reengineering tasks. By integrating the internet of things (IoT) technology and Efficiency Validate Analysis (EVA) simulation framework, this paper proposed a digital twin-enabled VSM approach for SMEs. This easy to adopt and accurate method helps manufacturing SMEs in redesigning and reengineering production processes. This study contributes to research on digital twin modeling, by proposing a theoretical framework which combines IoT data-driven production process planning and simulation methods. The novelty of this study also exists in proposing a comprehensive and practical solution for production process reengineering, which integrating the cutting-edge technologies including digital twin and IoT. The feasibility and validity of the proposed approach is proved by applying to a musical instrument factory in China.

In some semiconductor devices fabrication, the product manufacturing process need start with one implant layer, and then followed by a very thick epitaxial growth step. Unfortunately, first, it is not a manufacturable process to use the implant layer as the primary layer, second, the very serious mark distortion, which impacts alignment and OVL Metrology performance, is observed after wafer undergoing thick EPI process. This paper mainly focuses on these two challenges we came across as well as ways to address the issues related to lithography in the manufacturing process, focusing on the BCD production wafer.

The modelling of nominal product geometry by computer-aided design tools has gained immense attention in industry during the last decades and is nowadays an integral part of the virtual product development process. However, the established geometry representation schemes for CAD imply severe drawbacks regarding the modelling of geometric part deviations, which are inevitably observed on every manufactured artefact. As a response, the concept of Skin Model Shapes, which stems from international standards for geometric product specification and verification, has been developed as a novel approach for the consideration of product shape variability. It employs discrete geometry methods and computational techniques, such as point clouds, surface meshes and geometric processing, to model shape variability and to facilitate the communication of geometric product information throughout the product design, manufacturing, and inspection processes. This paper highlights the foundations of this concept, demonstrates its potentials for the representation of product geometry considering geometric variations along the product lifecycle, and illustrates main applications in the context of computer aided product and process development. In this regard, a focus is laid upon recent results and contributions, such as contact modelling, tolerance analysis, and motion tolerancing based on Skin Model Shapes. Furthermore, challenges for future research, such as the application to complex shapes and compliant parts, as well as the consideration of novel manufacturing processes, are discussed.

Data analytics plays a significant role in the realization of Industry 4.0. By generating context-related persistent datasets, every manufacturing process in real production becomes an experiment. The vision of Internet of Production (IoP) is to enable real-time diagnosis and prediction in smart productions by acquiring datasets seamlessly from different data silos. This requires interdisciplinary collaboration and domain-specific expertise. In this paper, we present a novel tool wear monitoring system for milling process developed in the context of IoP. This system is based on high-frequency data from the numerical control of the production machine without additional sensors. The novelty of this paper lies in the introduction of virtual workpiece quality and fusion of multiple build-in sensor signals and a force model as decision support. This bridges the time gap between quality inspection and production at the shop floor level, establishes an automated statistical process control system, and provides a more plausible prediction of tool lifetime. The monitoring of two different milling processes in a real production environment is exemplary demonstrated in this paper. The first case is a face roughing process with the aim of rapidly removing large amounts of material. The second case is a face finishing operation that follows roughing and aims to achieve the desired surface quality.

Gap Analysis and Optimization of Process Involved in Product Design and Development by Integrating Enterprise Resource Planning & Product Lifecycle Management

The assembly work constitutes a large percentage of the whole process of product manufacturing, assembly process planning is always one of the most difficult problems in manufacturing field. In this paper the authors will introduce a series of human centered thoughts and strategies on solving this problem which are realized in their prototype system. User's intents are captured by both the modalities of hands and eyes; Multiple perceptions and two hand concurrent manipulations are designed to acquire the interaction semantics and to deal with the most difficult cases of assembly; A new assembly model is put forward to support 3D interaction, and the method of using the real design data in the system is also introduced.

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Digital Library support for textual and certain types of non-textual documents has significantly advanced over the last years. While Digital Library support implies many aspects along the whole library workflow model, interactive and visual retrieval allowing effective query formulation and result presentation are important functions. Recently, new kinds of non-textual documents which merit Digital Library support, but yet cannot be fully accommodated by existing Digital Library technology, have come into focus. Scientific data, as produced for example, by scientific experimentation, simulation or observation, is such a document type. In this article we report on a concept and first implementation of Digital Library functionality for supporting visual retrieval and exploration in a specific important class of scientific primary data, namely, time-oriented research data. The approach is developed in an interdisciplinary effort by experts from the library, natural sciences, and visual analytics communities. In addition to presenting the concept and to discussing relevant challenges, we present results from a first implementation of our approach as applied on a real-world scientific primary data set. We also report from initial user feedback obtained during discussions with domain experts from the earth observation sciences, indicating the usefulness of our approach.

Flexible production line can meet the requirements of diversification and complexity of product processing and manufacturing process. According to the set process, the production and processing are combined together, and the automatic measurement, automatic control and continuous production are realized through online programming of the program. The system takes Siemens PLC controller as the core, combining with high-resolution servo motor, position sensor, material detection sensor and so on, in order to design the control system of automatic processing production line, realizing the functions of automatic transmission, feeding, loading and unloading, blanking, grabbing and positioning in the production process. The actual operation shows that the system has the advantages that manipulator grasp the workpiece firmly, the transmission line moving position is accurate, and the processing technology can be combined and changed, which can meet the high efficiency and high quality processing requirements of the production line.

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