Mold Industry Research Articles

Selective laser hardening of injection mould components on multi-axis machining centers

This research describes the selective laser hardening of components used in the injection moulding industry. The use of fiber-reinforced plastics is accompanied by increased wear in injection moulding tooling compared to conventional plastics. Selective hardening of locations in contact with these plastics prolongs the lifetime of these components. This paper focuses on selective laser hardening of two mould materials, stavax ESR and Sverker 21. Experiments are performed on a laser setup integrated into a multi-axis machining platform, allowing fabrication and hardening within one single clamping. Initial laser hardening tests were performed on ground samples consisting of the component base material. Microhardness measurements showed a maximum achieved hardness of 614HV for Stavax ESR and of 810HV for Sverker 21 after laser hardening. Following initial experiments, three injection moulding components, shredder blades, injection nozzles, and textured moulds are laser hardened.

Capital Structure Choices and Exports: the Case of the Portuguese Mold Industry

This paper analyses the impact of export’s intensity on capital structure choices of 647 Portuguese firms of the mold industry, for the period 2010-2017. Not only exports intensity variables are considered, but also variables to deal with firm specific characteristics and macroeconomic factors to fulfill the paper’s aim. Four alternative proxies of capital structure are used: total, long-term, short-term debt and bank loans. Analyzing an unbalanced sample of 4225 observations, using a panel data methodology and estimating the models with fixed effects for firms, the findings of the study reveal that the reliable determinants for leverage are asset structure, growth opportunities, non-debt tax shields, liquidity, risk, size, age and macroeconomic factors. Export’s intensity is only relevant to explain debt through bank loans, while export’s intensity to countries outside Europe is relevant to explain both total and short-term debt. The main results are consistent with the pecking order theory which propose a hierarchy of funds. The trade-off theory is also relevant. Finally, this study shows that firms from the mold industry are more indebted than other Portuguese firms (in mean), and short-term debt is more relevant in the total leverage of the firm.

Lean Six Sigma Approach to Improve the Production Process in the Mould Industry: a Case Study

Purpose: The purpose of this article is to explore the optimization of internal process is assumed as a critical factor to be capable of answering to the moulds industries. Consequently, it has been considered essential to adopt high-valued methodologies to support tooling industry in order to achieve global competitive advantages. For that purpose, this work aims to apply LEAN principles and techniques to support mould design and manufacturing processes.Methodology/Approach: The methodology used was based on PDCA/DMAIC, with the following stages: Define, Measure, Analyze, Improve and Control. For each stages was taken some of Lean Six Sigma techniques, such as Continuous Improvement, Value Stream Mapping, Pareto analysis and Overall Equipment Effectiveness.Findings: This study results was revealed that there are many areas on the organizations in the Mould Industry, when they utilize otimizations tools obtain hugt successes. With the Pareto analysis was carried out to show that events that contributes the most to the stops. The results were: unavailability of the operator (16.4%), programming the machine (14.4%) and tool exchange (12.4%) In the case of this Mould Industry study was obtained for the CNC machines studies, with the implementation of Lean Six Sigma tools as obtained a improvement about 20% of global OEE.Research Limitation/implication: This research was revealed that there the moulds are Project unique and difficult to analyze. Moreover, this paper reports that the approach LEAN Six Sigma is very interesting for the continuous improvement of processes and profitability of moulds industry.Originality/Value of paper: This research highlight areas of future research using of quality management methods and Lean Six Sigma tools to analyse and optimize production in the moulds industry. Therefore this research It is considered to promote and adopt high-valued methodologies to support tooling industry in order to achieve global competitive advantages.

Failure and Control of PCBN Tools in the Process of Milling Hardened Steel

The polycrystalline cubic boron nitride (PCBN) milling tool can be used in the mold industry to replace cemented carbide tools to improve machining efficiency and quality. It is necessary to study the tool wear and failure mechanism to increase machining efficiency and extend tool life. Cr12MoV is used to analyze the failure form of PCBN tools in the interrupted cutting of hardened steels at low and high speed conditions in milling experiments. Experimental results show that the failure forms of PCBN tools include chipping and flank wear at low speed, and the failure modes at high speed are flank wear, the surface spalling of the rake face, and the fatigue failure on the flank face. The failure mechanism of different failure forms is analyzed by observing the surface morphology of the tool and using the theory of fracture mechanics. The results show that a high cutting speed should be selected to avoid the early damage of low speed and achieve better application of PCBN tools. At high cutting speed, tool failure is mainly caused by mechanical wear, diffusion wear, and oxidation wear. Moreover, a fatigue crack will occur at the cutting edge on the chamfered tool under thermal–mechanical coupling because of the intergranular fracture of the CBN grain and binder. A large area of accumulated fatigue damage may appear due to the influence of alternating mechanical stress and thermal stress. Finally, the control method to avoid tool failure is presented.

Process Analysis on Milled Optical Surfaces in Hardened Stainless Steel

The capability to produce surfaces in optical quality is of rising prominence in the manufacturing industry. The die and mold industry have to meet rising requirements with regard to the surface finish and geometric precision, to keep pace with technological advances in sectors such as illumination, optical sensors, and fiber technology. This paper focuses on the challenges of developing a sample milling process for optical surface finishes in 53 HRC STAVAX stainless steel. Besides the expected process and tooling parameter variations, three prominent material analytics methods were used to evaluate all experiments. The tool wear was analyzed and monitored via SEM and EDS. To verify the milling process capabilities, a sample was produced through manual polishing and then analyzed for material faults via nanoindentation and BSE analysis. The finished results were measured for their surface roughness via bifocal laser microscopy and for their topography SEM. In the practical application, a surface roughness Ra in the single digit nano-meter range was achieved. A stable finishing process was achieved at high rotational speed with feed rates up to 750 mm/min. A practical cleaning solution with the use of a mild lye was found.

Numerical and experimental investigations of a conformally cooled maraging steel injection molding tool fabricated by direct metal printing

Costs and time are correlated greatly in the precision mold industries. To improve the productivity in series production, significant reduction in the cooling time is required. The profiled conformal cooling channel (PCCC) is a unique approach to reduce cooling time in the injection molding process compared with a conventional straight drilled cooling channel. In this study, a maraging steel injection molding tool with PCCC was manufactured by direct metal printing. Cooling performances of the injection molding tool with different methods were investigated via low-pressure wax injection molding. The part cooling time, part temperature difference, mold surface temperature difference, and product total deformation were modeled numerically using Moldex3D simulation software. It was found that the product cooling time for the injection molding tool with PCCC was reduced greatly. The product cooling time for the injection molding tool with PCCC, with gas cooling, and without cooling channels are 27 s, 94 s, and 543 s, respectively. The molding cycle time for the injection molding tool with PCCC about 93% can be saved compared with the injection molding tool without cooling channels. The molding cycle time of the injection molding tool with PCCC about 63.2% can be saved compared with the injection molding tool with gas cooling.

Cost control of mold enterprises under the trend of intelligence

The intelligentization of molds is an important development direction and frontier of molds at present, and the intelligentization of molds will have a huge impact on the development of the mold industry. Based on this, this paper first expounds the development background and cost structure of the mold manufacturing enterprise, then systematically analyzes the cost composition of the mold manufacturing industry, and finally proposes effective measures for the cost control of the mold manufacturing industry under the intelligent background.

Effect of laser-assisted nitriding with a high-power diode laser on surface hardening of aluminum-containing martensitic steel

The surface of steel molds used in injection molding must be particularly hard to withstand abrasive fiber-reinforced plastics. Thus, a laser nitriding process using a gas chamber setup is suggested as a surface modification process for the plastic mold industry in this study. The hardness distributions and microstructural evolution of AISI P21 steel after laser nitriding were fundamentally investigated and compared with the results of laser-assisted selective melting without nitrogen. After laser-assisted selective melting, the hardness had not changed relative to that of the base metal (410 HV), although the martensitic transformation had occurred in the melted zone. On the other hand, the laser-nitrided specimen (at 4500 mm/J of heat input) was approximately 40% (573 HV) harder than the base metal was before laser nitriding. In the region with increased hardness, an area with a high level of nitrogen was observed. In other words, nitrogen successfully penetrated into the surface of the specimen, and it formed a certain layer that corresponded well with the region of increased hardness. Moreover, the microstructure of the nitrogen condensed layer in Al-based nitride (AlN) was characterized by transmission electron microscopy. According to these results, the hardening behavior of AISI P21 steel after laser nitriding was mainly attributed to the development of the AlN phase.

곡면 병합을 이용한 금형 수정 가공의 단차 최소화

Die and mold are the most effective method for manufacturing parts. After a die or mold is used for a long time, it can be deformed or worn down or partly damaged. For the cases, it is welded with additional materials to be machined in repairing area with the original NC data for initial machining. However, this repairing process may cause microdrops at the boundary of repair machining area, since the used die might be deformed due to various reasons including residual stress or heat stress by welding, in addition to the error from the setup for the repair machining. This study is to develop a method to generate adapted NC data for repairing a deformed die, which can reduce the microdrops at the border of repair machining area. As a result, it cannot only negate or minimize the time and cost for removing the microdrops on repaired die surface but also can improve quality of the final products. Even though the proposed method was applied to dies for car body parts, it is not limited to the auto industry but can be extended to the other die and mold industries.

3D printed breathable mould steel: Small micrometer-sized, interconnected pores by creatively introducing foaming agent to additive manufacturing

Additive manufacturing & 3D printing has almost no limitation in realizing any geometry due to its layer-by-layer manufacturing manner, while producing small-sized, interconnected pores is one of its major challenges. In this study, we report that, by creatively combining additive manufacturing with foaming agent, interconnected pores (~26 vol.% porosity) with pore size of 2–30 μm have been successfully achieved. One of the most important applications of such unique structure is for developing the so-called breathable mould steel. Breathability is rather demanding for the mould industry, since it is capable to eliminate the trapped, detrimental gas during injection moulding and therefore much improve the quality of as-injected parts. It will be revealed by the study that, due to a good selection of the foaming agent (i.e. CrNx), the as-printed breathable steel has a great combination of compressive strength (~1.3 GPa), strain (~26%), microhardness (~360 HV) and corrosion resistance, along with sufficient breathability. These mechanical properties are even superior to the commercial PM-35 breathable steel. Based on detailed microstructural characterization, the affecting factors to the pore forming are studied, and the importance of the novel approach developed by the current study has been addressed.

Single machine scheduling problem with stochastic sequence-dependent setup times

In this study, we consider stochastic single machine scheduling problem. We assume that setup times are both sequence dependent and uncertain while processing times and due dates are deterministic. In the literature, most of the studies consider the uncertainty on processing times or due dates. However, in the real-world applications (i.e. plastic moulding industry, appliance assembly, etc.), it is common to see varying setup times due to labour or setup tools availability. In order to cover this fact in machine scheduling, we set our objective as to minimise the total expected tardiness under uncertain sequence-dependent setup times. For the solution of this NP-hard problem, several heuristics and some dynamic programming algorithms have been developed. However, none of these approaches provide an exact solution for the problem. In this study, a two-stage stochastic-programming method is utilised for the optimal solution of the problem. In addition, a Genetic Algorithm approach is proposed to solve the large-size problems approximately. Finally, the results of the stochastic approach are compared with the deterministic one to demonstrate the value of the stochastic solution.

Cutting Performance and Wear/Damage Characteristics of PCBN Tool in Hard Milling

In the intermittent machining of hardened steel for the die and mold industry, determining how to reduce the wear of PCBN (Polycrystalline Cubic Boron Nitride) tools and improve their machining efficiency and quality is an important subject. This study investigated the intermittent machining of hardened steel (Cr12MoV, 59HRC (Rockwell hardness)) using uncoated PCBN tools to determine the cutting performance (cutting force, chip morphology, surface quality, tool life, cutting temperature) and the wear/damage characteristics of the tools. The results showed that the cutting performance of a PCBN tool was better than that of a cemented carbide tool. The wear mechanism on the PCBN tool flank was diffusion wear, adhesive wear, and oxidation wear. The main failure modes of the PCBN tool in the machining process of hardened steel at low speed were tool micro-chipping, the conchoidal damage of the rake face, and the larger damaged area of the flank face. The main failure modes of the PCBN tool in the machining process of hardened steel at high speed were flank wear and high-rate fatigue damage.

Analysis of helium used as protective gas in Laser Metal Deposition of Ti6Al4V highly reactive material

Laser Material Deposition (LMD) is an additive manufacturing near-net-shape process. Metal powder particles are molten by means of a laser heat source and added to a substrate creating geometries. This technology offers the possibility of generating coatings, repairing damaged high-added-value parts, and manufacturing components with complex 3D geometries. Many industrial sectors, including aerospace and die and mold industries, are interested in this process due to its capabilities and the wide range of materials that can be used with it.Previous works aimed to develop a protective gas module to be able to process highly reactive materials without the necessity of a complete inert atmosphere inside the machine. Additionally, the influence of a mixture of argon and helium on the LMD process for other non-highly reactive alloys was evaluated. Hence, the present work aims to broaden the understanding of how the combination of these two factors may affect the LMD process, combining these previous studies and evaluating the phenomenon for a highly reactive alloy like Ti6Al4V. The study involves the melt-pool temperature measurement and characterization of the deposited clads variating not only the composition of the protective gas but also the flow rates.

An experimental investigation to optimise injection moulding process parameters for plastic parts by using Taguchi method and multi-objective genetic algorithm

Plastic injection moulding is a useful method to produce plastic parts with high-quality surface finish. Improper process parameter settings can cause many production troubles namely defective products, reduce dimensional precision and scrap. Thus, determining the optimal processing parameters is regularly performed in injection moulding industry. In this paper, to determine the initial range of process parameters steady state experiments were performed. Taguchi method and multi objective genetic algorithm are used to optimise the process parameters of electric meter box and to reduce its shrinkage and warpage and to enhance its impact strength. For this purpose L27 orthogonal array was used. The modified linear graph was used with the line separation method to assign the parameters and interactions to various columns of the orthogonal array. The confirmation experiments show that the errors associated with prediction of shrinkage, warpage and impact strength are 5.11%, 5.91% and 1.171% respectively.

金型産業における競争・分業構造 東アジア競争優位の研究

金型産業における競争・分業構造 東アジア競争優位の研究

An experimental investigation to optimise injection moulding process parameters for plastic parts by using Taguchi method and multi-objective genetic algorithm

Plastic injection moulding is a useful method to produce plastic parts with high-quality surface finish. Improper process parameter settings can cause many production troubles namely defective products, reduce dimensional precision and scrap. Thus, determining the optimal processing parameters is regularly performed in injection moulding industry. In this paper, to determine the initial range of process parameters steady state experiments were performed. Taguchi method and multi objective genetic algorithm are used to optimise the process parameters of electric meter box and to reduce its shrinkage and warpage and to enhance its impact strength. For this purpose L27 orthogonal array was used. The modified linear graph was used with the line separation method to assign the parameters and interactions to various columns of the orthogonal array. The confirmation experiments show that the errors associated with prediction of shrinkage, warpage and impact strength are 5.11%, 5.91% and 1.171% respectively.

Green fuzzy parallel machine scheduling with sequence-dependent setup in the plastic moulding industry

Green fuzzy parallel machine scheduling with sequence-dependent setup in the plastic moulding industry

Green fuzzy parallel machine scheduling with sequence-dependent setup in the plastic moulding industry

Job scheduling has always been a challenging task for production managers. It is of special importance if it involves multi-objectives and parallel machines. In this research, our direction is largely motivated by the uncertainty emerged in production systems, where processing times of jobs and setup times of machines are not fixed and they are subject to some uncertainties. Our paper presents a mixed-integer goal programming model considering fuzzy approach for parallel machines environments with separable jobs, sequence-dependent setup times and hazardous waste. Two fuzzy objectives are considered in the model to minimise the total tardiness and the total hazardous waste. Since the model is too complex to be solved using exact methods, we proposed a solution method based on genetic algorithm. To set the input parameters of the solution algorithm, Taguchi method is used. The results of the computational experiments indicate that the proposed algorithm is a proficient method and has efficiently found the optimal solutions for both objective functions.

Experimental Investigation of MQL Optimum Parameters in End Milling of AA6061-T6 using Taguchi Method

Minimum Quantity Lubricants is a technique in supplying small quantity of lubricant into machining area which also part of green manufacturing approach that receive wide attention globally. The main driven of introducing MQL method was due to negative environmental impact which leads to safety and health issues of conventional coolant among workers especially in tool and mould industries. Besides, based on research findings, the MQL system has the capability for lubricating and cooling both work piece and cutting tool. In order to find the best solution for machining and also to enhance machining performance, first and foremost the MQL parameters must be controlled wisely as it has remarkable effects on lubricant coverage, droplets size and subsequently influence the machining performance. Nozzle angle, nozzle distance and MQL flow rate are the important parameters studied and surface roughness is the response parameter. Therefore, in this study, MQL optimum parameters were explored by minimizing surface roughness in end milling process using Taguchi L9 orthogonal method. Aluminum Alloy 6061-T6 was selected as work piece material. The results show that the best combination of MQL parameters in minimizing surface roughness was obtained at 30mm nozzle distance, 30 degree nozzle angle and 1.98 mL/min MQL flow rate. Hence, based on this optimal condition, three confirmation runs were conducted. The margin error is acceptable which less than 10% and within prediction interval. This results can work as a base line guidance for any experimental that employ MQL system.

Cutting Force Model for Thermal-Assisted Machining of Tool Steel Based on the Taguchi Method

This paper investigates cutting force in thermal-assisted machining (TAM) by induction heating for SKD11 tool steel which is widely used in the mold industry. Experimental studies were first conducted at room and elevated temperatures to evaluate the effectiveness of the heating process on chip morphology and the cutting forces during the thermal-assisted machining and comparing with conventional machining method. The Taguchi method based on orthogonal array and analysis of variance ANOVA method was then used to design the number of experiments and evaluate the influence of cutting speed, feed rate, cutting depth, and elevated temperature on the cutting force. Study results showed a decrease in the cutting force in the TAM process. The optimal condition of parameters obtained for thermal-assisted machining were cutting speed 280 m/min, feed rate 230 mm/min, cutting depth 0.5 mm and temperature 400 °C. Finally, a proposed equation was established to determine the cutting force that was presented as a function of elevated temperatures when milling SKD11 material. A proposed cutting force model was compared, evaluated and confirmed to be in good agreement with experimental results.