Miniaturized optics are main components in many different areas ranging from smart devices over medical products to the area of automotive and mobility. Thus several million if not billions of small lenses are merged into objectives. The optical function of these objectives can only be guaranteed, if all optical surfaces not only meet the form tolerances of the optical design but also have the right position with respect to another. To ensure this, a measurement method has been developed, that is able to measure the surface form and the centration of both functional surfaces of single micro optical polymer lenses. The method bases on Optical Coherence Tomography (OCT) so that due to the tomographic measurement principle both functional surfaces can be captured in one measurement. Key challenge is the reconstruction of the geometric form of the functional surface facing away from the measurement head since it is distorted due to the refraction of light on the functional surface that faces towards the measurement head. The distortion needs to be corrected by means of backwards ray tracing. The OCT-based characterization of the single optical elements allows an adaptive assembly of micro optical imaging objectives by feeding back the individual shape of every single optical component to the assembly process. This information can be used for either selective assembly or the compensation of individual component tolerances by matching components whose form and centration errors cancel each other out in the overall system.
Active or sensor guided alignment presents a promising production approach for high-quality optical products and helps to overcome challenges in the tolerance chain. Application fields such as fast-axis collimation increasingly deploy automated productions solutions in order to improve and ensure stable quality even with relatively low production volume. The advantages are offset by the high demand towards the engineering as upfront cost, common to all automated production solutions with integrated evaluation of the system function. In this paper, we present our approach to overcome this problem. We propose the use of virtual environments, which are derived from empirical data generated with minimized effort in early phases of the product development. We will present options for building the necessary dataset and how our solution can derive an empirical simulation due to the application of artificial intelligence. Our solution is independent from ray tracing simulations and reflects defects, deviations and tolerances as observed in the actual product samples. This allows developing alignment algorithms offline, without the need for costly machine time and the risk of damage due to manual errors. We will present validation results, which demonstrates the capability to transfer active alignment algorithms from the virtual environment to actual automation equipment. Next to FAC alignment and the high-power laser industry our virtual environment solution is of special interest to application in the field of diffractive optical elements (DOE) and free-form optics, where low volume or changing designs demand adaptable automation solutions.
Due to their short focal lengths, FAC lenses significantly influence the performance of high-power diode laser systems. In addition to the shape, coating and surface quality, high demands are placed on the assembly accuracy for these microoptical components. In order to optimally align and position the lenses despite varying properties (e.g. focal length), active alignment strategies are used. The automation of the active alignment process for production offers enormous potential. Compared to manual processes, the reproducibility and accuracy of the alignment is increased. For the automation of the active alignment process, a deep understanding of the system behaviour is necessary. To control a diversity of variants cost-effectively and robust, new approaches must be taken into account. Concepts of AI or machine learning are great for this kind of generalization and adoption and they have many advantages for the active alignment of systems like DOEs or free-form-optics, with a complex system behaviour. In this publication, we want to compare the performance of a classically model-based algorithm and a machine learning approach for the automated active alignment of FAC-lenses. The model-based algorithm uses a physical model of the metrology system (including the FAC to be aligned) to estimate a misalignment in 4-DOF. The machine learning algorithm consist of a deep neuronal network which was trained with image data.
Polarization maintaining fibers arrays are key enablers to process high bandwidth data, representing a powerful part within the photonic integrated chip technology. The different channels increase the information density and allow to multiple singles through one fiber bulk at the same time. Due to fiber’s small dimensions (ø125 μm) they can be integrated in existing infrastructure easily and are very flexible at the same time. However, the compact design together with the flexible material properties demands for new precise tools and technologies to reach the necessary precision during packing.
The Fraunhofer-Institute for Production Technology IPT develops, together with their partners Phix and Aixemtec, new handling and assembly tools, as well as processes as one of the leading companies in this field. In the self-developed assembly cell, the fiber handling tool-head operations automatically to pick up, manipulate and tack single fibers to a glass plate or fiber to chip. Each fiber is moved by a portal robot within the assembly cell with micrometer accuracy but also can be rotated with a repetition accuracy less than 0.01°. Advanced illumination units observation techniques allow to package fibers arrays much quicker and more robust than before. Therefore, additional camera systems and material characteristics are used to develop smart alignment routines. As a result, the observation of the orientation of the PM-fiber core as well as the fiber layout during the assembly process leads to high quality products within fast production cycles. Due to the flexible construction of the assembly call also PIC packaging and fiber-to-chip coupling is possible.
Automated, ultra-precise packaging strategies reduce production time and costs while increasing yield, quantity, and precision, making them one of the main research and development questions in the field of production technology. Fraunhofer IPT develops sensor-guided assembly solutions for packaging and testing of optical and non-optical components to meet the demand. In this paper, we present a prototypical process for the automated, ultra-precise passive alignment using the assembly of a diamond engraving tool as an example. The challenge is to place a diamond measuring three millimetres in its largest dimension into a groove of similar size and to position the tip of the diamond within tolerances of a few micrometres and arcminutes. This six dimensional assembly problem is tackled by feeding live camera data to an image processing algorithm and by aligning the diamond using Fraunhofer IPT’s ultra-precise micromanipulator, collectively forming an automated, closed-loop assembly process. Thus, a fully automated packaging process with very high accuracy and reliability is proven to be technically possible.
KEYWORDS: Semiconductor lasers, Micro optics, Tolerancing, Assembly tolerances, Collimation, High power lasers, Control systems, Laser bonding, Active optics, Optical alignment, High power diode lasers
The industrial assembly processes for fast axis collimation (FAC) lenses with high power laser diodes are continuously being improved and automated. The system requirements allow for various solutions for the attachment process of the micro-optic component, the standard being active assembly relative to the light emitting laser-diode facet with joining by a UV-curable glue at attachment positions outside of the laser beam-path. To facilitate higher degrees of freedom and to optimize the results in the joining process with tighter tolerances in some critical functions, the FAC mounted on tab is one of the possible solutions and a viable process option. We report the results of high accuracy preassembly of FAC on tab with respect to the specific requirement of a target assembly back focal length within tight tolerance values.
Fast axis collimator (FAC) to Chip in the assembly of High Power Diode Lasers (HPDL) systems is state of the art done in active alignment. Micro manipulators and (semi-) automated machines are available for purchase on the market. Neither the precision of the manipulation tools (step resolution < 10 nm) nor the measurement systems utilized in active alignment algorithms (alignment precision of ~50 nm) are the quality limiting factors but the bonding process is. This is due to the volumetric shrinkage of fast curing UV-adhesives in the curing process.
The objective of this work is to reduce the absolute volume of adhesives in optical systems by smart design of the glue glap so no significant misalignment while curing is expected.
The assertion is that the overall system quality is improved with the implementation of additional adhesive gaps if the amount of adhesive is reduced in this way. In high quality systems as HPDL this approach is state of the art with the implementation of FAC lens on Bottom tab. In other industries as automotive sensors that are drastically reducing component tolerances and improving system quality this approach is rather unknown.
Results of glue gap reduction for HPDL assembly is described in this work by combining active alignment of FAC to edge emitter with a tolerance compensated individualized FAC on bottom tab subassembly in a fully automated production process. The approach was described in the papers [SPIE 10086-28] and [SPIE 10514-38].
Furthermore the approach of systemizing the smart glue gap design is done.
In micro-assembly of optical systems, active alignment can help to relax tolerances and guarantee optimal results for individual units by evaluating the actual system performance or suitable key-performance-indicators. Combined with capable micromanipulator technology bonding becomes the limiting factor in the overall assembly process. Due to unpredictable properties of the individual adhesive gap, volumetric shrinkage during curing is not sufficiently predictable for a robust compensation. In the past, Fraunhofer IPT presented curing-in-the-loop as a solution for increased precision in the bonding process. The measurement information from a preceding active alignment control loop can also serve as input during the bonding process. The observed and quantified shrinkage in the first moments of the curing process allows predicting the entire displacement due to volumetric shrinkage. A last correction step before the final curing dose leads the remaining shrinkage to approach the target pose. This curing-in-the-loop-strategy provides several parameters for tuning, which directly affect the achievable bonding strength. The segmentation in initial and final curing phase, the UV-doses, the time window to measure and evaluate and the amount of correction are just some examples. In this paper, we will present the bonding strategy and its parameters in detail and investigate the effects on the bonding strength of UV-cured adhesives. Especially the amount of correction during the curing process is an unknown process parameter.
Automated active alignment of optical components during the assembly process of optical systems is state of the art in today’s optics-production. With the increasing demand of optical systems in smart devices and automotive technologies, new methods and strategies have to be developed to guarantee rapid and goal-oriented development of active-alignmentalgorithms. A key approach to this is offline development via simulations. This paper presents and evaluates an efficient approach to generate a continuous data-feedback for the offline development of active-alignment-algorithms by interpolation of a discrete database. Dependent on the system-input the described procedure generates the raw, array-like output data of a CCD-chip from the existing data of the local neighborhood.
Injection moulding is key to fast mass production for smart devices, mobility and medical products, like micro-optics, covers and lab-on-a-discs respectively. For optics, several million if not billions of small lenses are merged into objectives. One characteristic type of objective holder is the lens barrel. The successful assembly of lenses with diameters of just a couple of millimetres into a lens barrel is an error-prone task antagonized with mass production and an optical inspection at the end of the assembly. Before the assembly and after the manufacture of the individual optics, the sprue separation takes place. This is a critical moment because even optics whose dimensions are within the target tolerance after manufacturing can be damaged by improper action. Common methods here are the separation by means of a blade, hot wire, laser or saw blade. Each of these methods has its advantages and disadvantages, but all have in common the introduction of stress and/or heat into the component. The Fraunhofer IPT investigates a much more elegant way removing the sprue from injection-moulded optics in an automated environment. Based on the ultrasound technology developed by IPT back in the 1980s, we use a high frequency generator to get an AC voltage and piezo crystal for the inverse piezoelectric effect. The crystal oscillates with a high frequency and low amplitude. Next, the λ/2 to λ/4 sonotrode amplifies the amplitude. The sonotrode is designed with a CAD model, simulated in ANSYS and the complete experimental verified on real lenses afterwards.
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