Real-Time Maintenance Policy in Manufacturing Systems With Intermediate Buffers

Real-time maintenance decision making in large manufacturing system is complex because it requires the integration of different information, including the degradation states of machines, as well as inventories in the intermediate buffers. In this paper, by using a discrete time Markov chain (DTMC) model, we consider the real-time maintenance policies in manufacturing systems consisting of multiple machines and intermediate buffers. The optimal policy is investigated by using a Markov Decision Process (MDP) approach. This policy is compared with a baseline policy, where the maintenance decision on one machine only depends on its degradation state. The result shows how the structures of the policies are affected by the buffer capacities and real-time buffer levels.

Joint Maintenance and Energy Management of Sustainable Manufacturing Systems

The expenses associated with maintenance activities and energy consumption account for a large portion of the total operation cost in manufacturing plants. Therefore, effective methods that can be used for smart maintenance decision-making and energy management to reduce the costs of these two sections and improve the competitiveness of manufacturing enterprise are of high interests to industry. Many efforts focusing on maintenance decision-making and energy management have been dedicated. However, most of the existing research focusing on these two topics has been conducted separately, very little work has been done from a joint perspective that considers the benefits from both manufacturing machine reliability improvement and energy cost reduction. In this paper, a joint maintenance and energy management method is proposed to identify the maintenance actions considering energy cost as well as other equipment health metrics. A numerical case based on a section of an automotive assembly line is used to illustrate the potential benefits of the proposed approach.

Cloud Manufacturing Resource Management Based on Metadata

Centralized management and sharing of manufacturing resources is one of the important functions of cloud manufacturing platform. There are many kinds of manufacturing resources, centralized management, optimized scheduling, quick searching for various manufacturing resources become important issues in a cloud manufacturing platform. This paper presents a resource management model based on metadata to realize the access and unified management of the hardware resources, software resources and knowledge resources. Two management approaches respectively for static and dynamic resource data are introduced to realize resource state monitoring and real-time information collecting. On this basis, the relationship between static and dynamic data is determined and service-oriented of resources is realized.

Tool Wear Monitoring for Ultrasonic Metal Welding of Lithium-Ion Batteries

This paper presents a tool wear monitoring framework for ultrasonic metal welding which has been used for lithium-ion battery manufacturing. Tool wear has a significant impact on joining quality. In addition, tool replacement, including horns and anvils, constitutes an important part of production costs. Therefore, a tool condition monitoring (TCM) system is highly desirable for ultrasonic metal welding. However, it is very challenging to develop a TCM system due to the complexity of tool surface geometry and a lack of thorough understanding on the wear mechanism. Here, we first characterize tool wear progression by comparing surface measurements obtained at different stages of tool wear, and then develop a tool condition classification algorithm to identify the state of wear. The developed algorithm is validated using tool measurement data from a battery plant.

Subsurface Deformation in Surface Mechanical Attrition Processes

A modified expanding cavity model (M-ECM) is developed to describe subsurface deformation for strain-hardening materials loaded in unit deformation configurations occurring in surface mechanical attrition. The predictive results of this model are validated by comparison with unit deformation experiments in a model material, oxygen free high conductivity copper, using a custom designed plane strain deformation setup. Subsurface displacement and strain fields are characterized using in-situ digital image correlation. It is shown that conventional analytical models used to describe plastic response in strain-hardening metals are not able to predict important characteristics of the morphology of the plastic zone, including evolution of the dead metal zone (DMZ), especially at large plastic depths. The M-ECM developed in the present study provides an accurate prediction of the strain distribution obtained in experiment and is of utility as a component in multi-stage process models of the final surface state in surface mechanical attrition.

Analytical Modeling of Ultrasonic Vibration Assisted Drilling of Bones for Medical Surgical Applications

This paper presents a new analytical modeling of ultrasonic vibration assisted drilling of bones for medical surgery operations. Due to the heterogeneous bone structure and the uneven bone surface, bone surgery cutting suffers from inaccuracy and difficulty in high precision bone surgery cutting. In this paper, a new method of ultrasonic vibration assisted drilling is proposed for bone surgery cutting. An analytical force modeling is presented for ultrasonic vibration assisted bone drilling. Experimental result validates the analytical modeling presented in the paper. Preliminary testing result also shows a significant improvement of drilling accuracy based on the proposed ultrasonic vibration assisted bone drilling. The proposed cutting techniques can be used in bone cutting surgery to increase the accuracy of born drilling position and reduce trauma damage of bone and surrounding soft tissues.

Selective Laser Foaming for Three-Dimensional Cell Culture on a Compact Disc

A selective laser foaming process is developed to fabricate three-dimensional (3D) scaffold on a commercially available compact disc (CD) made of polycarbonate (PC). The laser-foamed 3D structure could be utilized to form high throughput perfusion-based tissue model device. In this study, effects of significant parameters and the morphology of porous structure were analyzed. As a result, laser foaming of gas saturated polycarbonate creates inverse cone-shaped wells with 3D porous structure on the surface region and the pores are tens of micrometers in diameter. The size of the well is dependent on the laser power and laser exposure time. The pore size relies on the gas concentration in the PC CD samples. The fabricated micro-scale porous scaffolds will be used to create centrifugal force driven two-chamber tissue model system arrays for high throughput drug testing.

Investigation of Acoustic Signals During W1 Tool Steel Quenching

Quenching is an important part of the heat treatment process for strengthening medium and high carbon steels. In the heat treatment cycle, the metal is heated to a desired temperature (above the eutectoid temperature) in the furnace and then cooled in a fluid medium such as water, brine, oil or air. Depending on the cooling rate, the mechanical and metallurgical properties of the metal can be altered in order to achieve the specific design parameters that are required by the part. The process in which the metal is cooled rapidly is termed the quenching process. Due to rapid cooling in a medium, such as water, brine, or oil, the quenching process produces an audible sound signature, as well as, acoustic emissions. In this paper, W1 tool steel is investigated through the use of a beam former that is equipped with 32 microphones. Using this device, it is demonstrated that the audible sounds that are produced when quenching depend on the heat treatment temperature and the size of the specimen.

Parameter Estimation Using Markov Chain Monte Carlo Method in Mechanistic Modeling of Tool Wear During Milling

Several models have been proposed to describe the relationship between cutting parameters and machining outputs such as cutting forces and tool wear. However, these models usually cannot be generalized, due to the inherent uncertainties that exist in the process. These uncertainties may originate from machining, workpiece material composition, and measurements. A stochastic approach can be utilized to compensate for the lack of certainty in machining, particularly for tool wear evolution. The Markov Chain Monte Carlo (MCMC) method is a powerful tool for addressing uncertainties in machining parameter estimation. The Hybrid Metropolis-Gibbs algorithm has been chosen in this work to estimate the unknown parameters in a mechanistic tool wear model for end milling of difficult-to-machine alloys. The results show a good potential of the Markov Chain Monte Carlo modeling in prediction of parameters in the presence of uncertainties.

Fabrication of 3D Scaffolds via E-Jet Printing for Tendon Tissue Repair

Current clinical grafts used in tendon treatment are subject to several restrictions and there is a significant demand for alternative engineered tissue. The previously reported tendon scaffolds mainly based on electrospinning and textile technologies showed promising results for tendon regeneration. However, limitations, such as small pore size, nutrition transmission, cell attachment, exist universally in such scaffolds. In this work, a novel tissue engineered polycaprolactone (PCL) tendon scaffold based on electrohydrodynamic jet printing (E-Jetting) was developed for investigation. In preliminary in-vitro study, human tenocytes were seeded in scaffolds with pore size of ∼106 μm to investigate the cell attachment, morphology and alignment. This study suggested that E-jetted tendon scaffold highly mimicked hierarchical construction from fiber to fascicle level of the native tendon, and has potential to be an alternative tendon regeneration tool.