Mould-making Industry Research Articles

Evaluation of bonding integrity of hybrid-built AlSi10Mg-aluminium alloys parts using the powder bed fusion process

Recent advances in metal additive manufacturing (AM) technology enable complex conformal cooling channels to be fabricated for injection and blow mould inserts. However, high manufacturing costs hinder the technology being adopted in the mould-making industry. A cost-effective hybrid strategy was developed for the powder bed fusion (PBF) process in which powder materials get additively deposited onto pre-machined substrates as a practical cost-reduction solution. In this study, the interface bonding integrity, in terms of microstructure and mechanical properties, of powder AlSi10Mg and three types of substrate aluminium alloys were evaluated. Microstructure analysis revealed excellent powder-substrate fusion across the narrow interface of the three samples. All tensile specimens ruptured at least 5 mm away from the bonded interface, at the side where the material was of lower strength. Samples fabricated with AlSi10Mg-Alumec 89 alloys had the highest tensile strength of 481 MPa, about the same as standard as-built AlSi10Mg aluminium. Using the PBF-machined substrate hybrid AM strategy, Alumec 89, a high strength tooling-grade aluminium alloy, can be used as the base substrate for the fabrication of durable and high-performance aluminium injection and blow mould inserts.

A machined substrate hybrid additive manufacturing strategy for injection moulding inserts

In recent years, advances in metal additive manufacturing (AM) technology make the fabrication of complex conformal cooling channels for injection mould possible. However, poor surface finish, inadequate dimensional accuracy, and high manufacturing costs impede the technology to be adopted in the mould-making industry as an alternative. In this study, a time-efficient machined substrate hybrid AM strategy was developed for the fabrication of injection mould inserts using a hybrid additive-subtractive powder bed fusion process. The primary goal is to reduce AM build and post-processing time. Pre-machined support-free substrate blocks with position alignment and referencing features for subsequent machining operations were used for the additive manufacturing and high-speed machining processes. Four mould inserts, selected from a production injection mould, were redesigned with conformal cooling channels and fabricated in a metal powder bed fusion system using the standard AM practice and the proposed hybrid-build method. In comparison with the standard AM practice, a considerable saving in processing time was attained, but with a slight compromise in tensile strength. Through optical microscopy (OM) and scanning electron microscopy (SEM), a strong fusion bonding can be seen at the interface boundary between the additive powder and machined substrate. This new strategy will provide mould performance enhancement at reduced manufacturing costs for the plastic products manufacturing industry.

A cloud-based, knowledge-enriched framework for increasing machining efficiency based on machine tool monitoring

The ever-increasing complexity in manufacturing systems caused by the fluctuating customer demands has highly affected the contemporary shop-floors. The selection of the appropriate cutting parameters is becoming more and more challenging due to the increasing complexity of products. Until now, the knowledge of the machine operators concerning the modification of the machining parameters and the monitoring information is not sufficiently exploited by the optimization systems. Web and Cloud technologies together with wireless sensor networks are required to capture the shop-floor data and enable the ubiquitous access from multiple IT tools. For addressing these challenges, this research work proposes a Cloud-based, knowledge-enriched framework for machining efficiency based on machine tool monitoring. More precisely, it focuses on the optimization of the machining parameters and moves through an event-driven optimization algorithm, utilizing the existing machining knowledge captured by the monitoring system. Based on the features of a new part, a similarity mechanism retrieves the cutting parameters of successfully executed past parts that have been machined. Afterwards, the optimization module, using event-driven function blocks, adapts these parameters to efficiently optimize the moves and the cutting parameters. The monitoring system uses a wireless sensor network and a human operator input via mobile devices. A case study from the mould-making industry is used for validating the proposed framework.

A mobile application for knowledge-enriched short-term scheduling of complex products

The ever-increasing product complexity, especially for the case of engineer-to-order products, highly affects the performance of manufacturing systems. Therefore, a high degree of flexibility is needed during daily decision-making activities, such as production scheduling. For addressing this challenge, this research work proposes a knowledge-enriched short-term job-shop scheduling mechanism, which is implemented into a mobile application. More precisely, it focuses on the short-term scheduling of the resources of the machine shop, through an intelligent algorithm that generates and evaluates alternative assignments of resources to tasks. Based on the requirements of a new order, a similarity mechanism retrieves successfully executed past orders together with a dataset that includes the processing times, the job and task sequence, and the suitable resources. In addition to that, the similarity mechanism is used to calculate the due-date assignments of the orders based on the knowledge stored in past cases. Afterwards, it adapts these parameters to the requirements of the new order so as to evaluate the alternative schedules and identify a good alternative in a timely manner. The deriving schedule can be presented on mobile devices, and it can be manipulated by the planner on-the-fly respecting tasks precedence constraints and machine availability. A case study from the mould-making industry is used for validating the proposed method and application.

PSS Design Evaluation via KPIs and Lean Design Assistance Supported by Context Sensitivity Tools

Over the last decade, Product-Service System (PSS) has been established as a prominent business model which promises sustainability for both customers and organizations. A great amount of literature work has been devoted to PSS issues, but there is fairly limited published work on integrated and easily applicable evaluation methodologies for PSS design, as well as lack of Lean PSS approaches. Contributing to these directions, the present work introduces a conceptual methodology for the evaluation and improvement of the PSS design procedure using Key Performance Indicators (KPIs) and Lean rules respectively, applied throughout all stages of PSS design lifecycle. The methodology contains two phases: i) PSS design evaluation, and ii) Lean PSS design assistance. According to the evaluation phase, a certain appropriate set of KPIs is selected and suggested to the PSS designer via a context sensitivity analysis (CSA) tool through a pool of 170 KPIs, which have been identified after intensive literature survey, and systematically classified into four main categories: Design, Manufacturing, Customer, and Environmental. From the collected and classified KPIs, a successive grouping is carried out of those KPIs that contribute to the Sustainability of the designed PSS offering. During the phase of Lean design assistance, Lean Rules are selected using CSA, and suggested to the designer at all design steps to ensure the minimization of wasteful activities. Enabler for the context awareness is the availability of feedback gathered from the manufacturing, shop-floor experts and the different types of Customers (Business or final-product Customers), as well as the PSS lifecycle stages which the designer treats. An ontology knowledge model for KPIs and Lean rules is proposed to support the CSA. The methodology is discussed in a case study of the PSS design from a mould-making industry.

Lean Rules Identification and Classification for Manufacturing Industry

Lean theory, principles and tools, are intended to highlight the value within the company and eliminate waste entirely. Despite the large amount of literature work on lean, there is a lack of in-depth analysis for collection and categorization of specific lean rules for the manufacturing industry. Therefore, the present work proposes a classification, formalization and identification of lean rules, in order to create a comprehensive and applicable library of lean rules, after the investigation of academic literature and a mould-making industry. Finally, the “drawer” idea is introduced aiming to motivate employees of different hierarchical levels in the lean rules development.

Industrial Big Data as a Result of IoT Adoption in Manufacturing

The radical evolution of internet into a network of interconnected objects that create a smart environment is characterized by the term Internet of Things (IoT). The adoption of IoT in manufacturing enables the transition of tradition manufacturing systems into modern digitalized ones, generating significant economic opportunities through industries re-shaping. Industrial IoT empowers the modern companies to adopt new data-driven strategies and handle the global competitive pressure more easily. However, the adoption of IoT, increases the total volume of the generated data transforming the industrial data into industrial Big Data. The work demonstrated in this paper presents how the adoption of IoT in manufacturing, considering sensory systems and mobile devices, will generate industrial Big Data. Moreover, a developed IoT application is presented showing how real industrial data can be generated leading to Industrial Big Data. The proposed methodology is validated in a real life case study from a mould-making industry.

A Parametric study of radial tool actuation in orbital EDM

Electrical discharge machining (EDM) has become a widely used nonconventional machining process in aerospace and die-/mould-making industries. This machining process is capable of machining any electrically conductive material irrespective of its hardness. This machining process requires identical shape of tool electrode with the cavity to be generated, which increases the requirement of tool electrodes. The requirement of tool electrodes can be reduced by the actuating the tool electrode on X, Y and Z axes, this is also called orbiting of tool electrode. The path of tool actuation may follow helical, radial, cylindrical path, etc. In the present investigation, circular hole is generated using radial tool actuation in EDM. An attempt has been made to study the effect of orbital parameters such as orbital radius and orbital speed on material removal rate (MRR). Experiments have been designed using Taguchi L9 orthogonal array. Using signal-to-noise ratio, analysis of variance results have been analysed. The results indicate that MRR varies with both orbital radius and orbital speed.

Knowledge-based Estimation of Manufacturing Lead Time for Complex Engineered-to-order Products

Product complexity leads to increased unpredictability of indices related to manufacturing performance estimation. This phenomenon is intensified in companies that produce engineered-to-order products, such as the knowledge and labour intensive mould-making industry. During the initial capturing of product specifications formalisation difficulties arise. Moreover, the estimation of delivery times for new moulding project is solely based on the engineers’ experience. A methodology, which has been developed into a software tool is proposed that exposes graphical interfaces for customers to submit new orders and establish a formalised communication with the engineering team. The collected data are stored in a knowledge repository and are processed by a case-based reasoning mechanism for the lead time estimation. A real-life pilot installation has been initiated to a mould making SME. Preliminary results depict a significant reduction in the number of iterations between customers and engineering department compared to the traditional approach followed by the company, and improved accuracy of lead time estimation.

Intrinsic innovations of die sinking electrical discharge machining technology: estimation of its impact

The die sinking version of electrical discharge machining (EDM) is a current manufacturing technology widely disseminated in several industrial sectors. In the recent past, developments in the high-speed milling (HSM) have narrowed the EDMs’ traditional application domains. As a result, a strong research effort has been focused on EDM leading to the reduction of the operation time and cost and to the increase of final surfaces quality. To identify future trends and perspectives of development within the industrial application of EDM technology, a survey was conducted among mould-making industrial companies and EDM equipment manufactures. The survey was designed to allow the exposure of the most relevant weaknesses and strengths of the technology and the identification of short-term threats and opportunities. In parallel, the expected impacts of the most recent developments of conventional EDM were assessed. To structure and systematize the overall analysis and quantify the total impact of each technologic innovation, a criteria matrix evaluation method was used. The results show that EDM technology will be kept as a reference manufacturing process in the mould-making industry. The maximization of EDM advantages in domains that no other technology can effectively achieve (complex geometries and hard materials processing) is one of the main reasons pointed out for the sustainability of EDM future competitiveness. The other reasons are the reduction of operative and set-up time, the reduction of operator intervention, and the extension toward surface-polishing operations.

Mould data management in plastic injection mould industries

In the current mould-making industries, the challenge is to shorten the mould lead-time while maintaining the desired quality. This is one of the main demands from customers so as to maintain a competitive edge over the competition. While mould industries are always improving on their systems to cater to the rapidly changing plastics industry, one of the common issues that are still plaguing them is the management of large quantities of data within a mould project. In the current practice of local mould-making industries, almost all the data for the mould design, manufacture and testing stage are often either confused or duplicated unnecessarily. As a result, it becomes less responsive when changes are required since manual decision-making and sorting of these data are required. With the increasing complexity of plastic part design, the corresponding mould design, manufacturing, and testing data also increase in both quantity and complexity. The usual method of managing these data would take up a substantial amount of time. This issue could be resolved by incorporating a data management system that specifically caters to mould-making industries into their practice. This paper presents a framework for how the data from the different stages of the mould project could be managed more efficiently through the use of templates. This framework is divided into modules to cater for the various stages of the mould project. A case study is presented to illustrate the proposed framework for mould data management.

A template approach to manage mould-testing stage in a plastic injection mould project

Two major tasks are involved in the mould-testing process stage for any mould project: (a) to troubleshoot and make decisions during the internal/external mould-testing; and (b) to perform dimensional inspection of satisfactory moulded parts. In any plastic injection mould industries, the mould-testing process stage is often the most hectic. The main reasons behind the buzz of activities are that enormous amounts of data need to be sorted and managed and decisions have to be made dynamically. The mould-making industries also rely heavily on field experts during the decision-making of the mould-testing process stage. It is both time-consuming and unproductive to manage the large amount of data, and sending field experts overseas to oversee the mould-testing and to make decisions is an expensive fraction on the company's expenses. The template approach can be executed to overcome the problems faced. The reason being that the expertise on the decision-making during the mould-testing is not unique. These expertises can easily be consolidated into a knowledge database and novice personnel could simply obtain the information from there and make similar decisions as the field experts. This template approach also offers an avenue to manage the data systematically through a proper channel of recording the necessary information without duplication. A case study was also presented to demonstrate the use of templates in managing the mould-testing stage of a mould project.

Design and NC Machining of Concave-Arc Ball-End Milling Cutters

The paper presents a geometric modelling approach for the precision design and NC machining of a concave-arc ball-end milling (CABEM) cutter which is an important tool for mould-making industries. This paper presents systematic models of the cutting edge, helical groove, and grinding wheel design for the NC machining of a CABEM cutter. Both the normal to the revolving axis and the tangent to the groove, are used to derive the required precision sectional profiles of the grinding wheel. In compliance with the maximal sectional radius of the cutter, the profile of the groove section and both the radial and axial cutting speeds of the grinding wheel are computed in sequence. Using the computer simulation results of the groove actually obtained, this paper proposes a method to resolve the problems of the residual revolving surface and the narrow cutting edge strip. This paper is intended to serve as a reference for the design and NC machining of cutters of this type.

Precision design and numerical control machining of tapered ball-end milling cutters

The paper presents a systematic modelling approach for precision design and numerical control (NC) machining of the tapered ball-end milling (TBEM) cutter that has emerged as a powerful tool for mould-making industries. The major contribution of this work is to produce a complete cutting edge that was conventionally neglected or oversimplified near the ending portion interfacing with the tapered ball end. In order to comply suitably with the requirement for a specific rotating speed, both radial and axial cutting speeds are carefully derived by using a given helical angle defined as the angle between the cutting edge and the revolving axis. Both projected profiles, one normal to the revolving axis and the other tangential to the groove, are used to produce precision sectional profiles of the grinding wheel. In compliance with maximal sectional radius of the taper, the profile of the groove section and the feeding speed of the grinding wheel are computed in sequence. By means of a two-axis NC machine, the shape of the TBEM cutter that possesses a nearly constant helical angle can be systematically designed and produced. With a slightly remedial grinding procedure at the ball end, the dimensional accuracy of the groove and the cutting edge of the TBEM cutter can be well controlled.