Hasil untuk "Manufactures"

K. Ferdows, A. Meyer

Abstract Is there a way to avoid trading off one capability for another in manufacturing? The prevailing wisdom says no. But some manufacturers seem to have been able to defy that: compared to their competitors, they have better quality, are more dependable, respond faster to changing market conditions and in spite of all that, achieve lower costs. How can this be explained? Our aim here is to provide an explanation. We contend that the nature of the trade-offs among manufacturing capabilities is more complex than has been assumed. Depending on the approach taken for developing each capability, the nature of the trade-offs change. In certain cases not only can trade-offs be avoided altogether, but in fact one capability would enhance another. They become cumulative. Moreover, when a capability is developed in this way, it is likely to be more lasting and less fragile than if it were developed at the expense of other capabilities. We go on to suggest a model which shows how this can be done: To build cumulative and lasting manufacturing capability, management attention and resources should go first toward enhancing quality, then—while the efforts to enhance quality are further expanded—attention should be paid to improve also the dependability of the production system, then—and again while efforts on the previous two are further enhanced—production flexibility (or reaction speed) should also be improved, and finally, while all these efforts are further enlarged, direct attention can be paid to cost efficiency. We use data from 1988 European Manufacturing Futures Survey (167 respondents) to test and illustrate our model. While we cannot “prove” our model, nevertheless, we believe there is enough evidence for a critical reexamination of traditional managerial approaches for improving manufacturing performance. For example, except for the cases when there are obvious slacks in the production system, the belief that costs can come down quickly and lastingly needs to be questioned. Lasting cost efficiency in production can be achieved only through improvements in other capabilities.

M. Mehrabi, A. Galip Ulsoy, Y. Koren

Jeffrey Miller, A. Roth

T. Hill

Eve D. Rosenzweig, A. Roth, J. Dean

K. Bunse, M. Vodicka, P. Schönsleben et al.

E. Atzeni, A. Salmi

W. ElMaraghy, H. Elmaraghy, T. Tomiyama et al.

Hyub Lee, Chin Huat Joel Lim, Mun Ji Low et al.

T. Mukherjee, J. Zuback, A. De et al.

Although additive manufacturing (AM), or three dimensional (3D) printing, provides significant advantages over existing manufacturing techniques, metallic parts produced by AM are susceptible to distortion, lack of fusion defects and compositional changes. Here we show that the printability, or the ability of an alloy to avoid these defects, can be examined by developing and testing appropriate theories. A theoretical scaling analysis is used to test vulnerability of various alloys to thermal distortion. A theoretical kinetic model is used to examine predisposition of different alloys to AM induced compositional changes. A well-tested numerical heat transfer and fluid flow model is used to compare susceptibilities of various alloys to lack of fusion defects. These results are tested and validated with independent experimental data. The findings presented in this paper are aimed at achieving distortion free, compositionally sound and well bonded metallic parts.

I. Colao, R. Corteling, D. Bracewell et al.

I. S. Jawahir, H. Attia, D. Biermann et al.

K. Prakash, T. Nancharaih, V. Rao

Rujian Sun, Liuhe Li, Ying Zhu et al.

R. Kunert, D. Reinhart

Since the first use of Chinese hamster ovary (CHO) cells for recombinant protein expression, production processes have steadily improved through numerous advances. In this review, we have highlighted several key milestones that have contributed to the success of CHO cells from the beginning of their use for monoclonal antibody (mAb) expression until today. The main factors influencing the yield of a production process are the time to accumulate a desired amount of biomass, the process duration, and the specific productivity. By comparing maximum cell densities and specific growth rates of various expression systems, we have emphasized the limiting parameters of different cellular systems and comprehensively described scientific approaches and techniques to improve host cell lines. Besides the quantitative evaluation of current systems, the quality-determining properties of a host cell line, namely post-translational modifications, were analyzed and compared to naturally occurring polyclonal immunoglobulin fractions from human plasma. In summary, numerous different expression systems for mAbs are available and also under scientific investigation. However, CHO cells are the most frequently investigated cell lines and remain the workhorse for mAb production until today.

Muhammad Syafrudin, Ganjar Alfian, Norma Latif Fitriyani et al.

With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as Internet of Things (IoT)-based sensors can be considered a solution to provide efficient monitoring of the manufacturing process. In this study, a real-time monitoring system that utilizes IoT-based sensors, big data processing, and a hybrid prediction model is proposed. Firstly, an IoT-based sensor that collects temperature, humidity, accelerometer, and gyroscope data was developed. The characteristics of IoT-generated sensor data from the manufacturing process are: real-time, large amounts, and unstructured type. The proposed big data processing platform utilizes Apache Kafka as a message queue, Apache Storm as a real-time processing engine and MongoDB to store the sensor data from the manufacturing process. Secondly, for the proposed hybrid prediction model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based outlier detection and Random Forest classification were used to remove outlier sensor data and provide fault detection during the manufacturing process, respectively. The proposed model was evaluated and tested at an automotive manufacturing assembly line in Korea. The results showed that IoT-based sensors and the proposed big data processing system are sufficiently efficient to monitor the manufacturing process. Furthermore, the proposed hybrid prediction model has better fault prediction accuracy than other models given the sensor data as input. The proposed system is expected to support management by improving decision-making and will help prevent unexpected losses caused by faults during the manufacturing process.

Sanika Doolani, Callen Wessels, Varun Kanal et al.

Recently, the use of extended reality (XR) systems has been on the rise, to tackle various domains such as training, education, safety, etc. With the recent advances in augmented reality (AR), virtual reality (VR) and mixed reality (MR) technologies and ease of availability of high-end, commercially available hardware, the manufacturing industry has seen a rise in the use of advanced XR technologies to train its workforce. While several research publications exist on applications of XR in manufacturing training, a comprehensive review of recent works and applications is lacking to present a clear progress in using such advance technologies. To this end, we present a review of the current state-of-the-art of use of XR technologies in training personnel in the field of manufacturing. First, we put forth the need of XR in manufacturing. We then present several key application domains where XR is being currently applied, notably in maintenance training and in performing assembly task. We also reviewed the applications of XR in other vocational domains and how they can be leveraged in the manufacturing industry. We finally present some current barriers to XR adoption in manufacturing training and highlight the current limitations that should be considered when looking to develop and apply practical applications of XR.

Morteza Ghobakhloo

This study aims to identify and analyse factors that determine the implementation of Information and Digital Technologies (IDT) of smart manufacturing. By performing a state-of-the-art and content-driven review of literature, consulting a group of experts from academia and industry, and implementing interpretive structural modelling methodology, the study identified eleven enabling factors and mapped the contextual interrelationships among them. The study further explained the complex precedence relationships that exist among determinants of smart manufacturing IDT adoption. Results showed that perceived benefits and management support are the two driver determinants that act as stepping-stones in the implementation of smart manufacturing IDT. Operations technology maturity and cybersecurity maturity were found to be the dependent determinants of smart manufacturing IDT implementation and highly driven by the linkage and driver determinates. The findings are expected to assist academicians, industrialists, and the policymakers with achieving a detailed understanding of smart manufacturing transformation processes, and conditions that facilitate the manufacturing digitalisation in the Industry 4.0 era.

L. Thames, Dirk Schaefer

Abstract Many of the world's leading industrial nations have invested in national initiatives to foster advanced manufacturing, innovation, and design for the globalized world. Much of this investment has been driven by visions such as Industry 4.0, striving to achieve a future where intelligent factories and smart manufacturing are the norm. Within this realm, innovations such as the Industrial Internet of Things, Cloud-based Design and Manufacturing (CBDM), and Social Product Development (SPD) have emerged with a focus on capitalizing on the benefits and economies of scale provided by Internet Protocol (IP) communication technologies. Another emerging idea is the notion of software-defined systems such as software-defined networks, which exploit abstraction and inexpensive hardware advancements in an effort to build more flexible systems. Recently, the authors have begun considering how the notion of software-defined systems might be harnessed to achieve flexible cloud manufacturing systems. As a result, this paper introduces the notion of Software-Defined Cloud Manufacturing (SDCM). We describe a basic SDCM architecture based on leveraging abstraction between manufacturing hardware and cloud-based applications, services, and platforms. The goal of SDCM is to advance Cloud-Based Manufacturing and other Industry 4.0 pillars by providing agility, flexibility, and adaptability while also reducing various complexity challenges.

Yotam Katzman, Mor Elgarisi, Amos A. Hari et al.

The conventional manufacturing of ophthalmic lenses is an inefficient subtractive process where up to 97% of the material is discarded through grinding, polishing, and edging. Fluidic Shaping has emerged as a powerful alternative, utilizing surface tension to form optical-quality surfaces. While the approach enabled the creation of ophthalmic lenses without grinding or polishing, it was limited to lenses with a circular or elliptical footprint and still required the wasteful edging process to fit the lenses into the eyewear rims. Here, the Cookie Cutter algorithm is introduced, generalizing the Fluidic Shaping approach to be applicable to arbitrary domains, thus eliminating all subtractive processes. This mathematical framework calculates the unique varying edge-height required for a boundary frame, allowing a liquid polymer to naturally settle into a target spherocylindrical prescription within an arbitrary rim footprint. By utilizing neutral buoyancy to negate gravity, the liquid polymer is shaped solely by surface tension and subsequently cured, resulting in a lens that fits directly into commercial eyewear rims without any mechanical post-processing. The method is validated experimentally, demonstrating the fabrication of lenses compatible with standard eyewear rims. This approach represents a complete additive manufacturing solution, enabling end-to-end zero-waste production of prescription eyeglasses.