Shrinkage and Warpage in the Permanent Shape of Sape-Memory Polyurethane Parts

The shape memory effect, as the most important ability of shape memory polymers, is a working property and provides the design ability to shape memory polymer features. Shrinkage and warpage are important parameters to control the dimensional accuracy of permanent and temporary shapes of an injection moulded shape memory polyurethane (SMPU) part. In this study, the effects of injection moulding parameters on the shrinkage and warpage of the permanent shape of moulded SMPU parts were experimentally investigated. The parameters of injection pressure, melt temperature, mould temperature, packing pressure, packing time, and cooling time, were chosen as the injection moulding control factors. Taguchi�s L27 orthogonal array design table was used with six injection moulding parameters and their three levels. The results showed that the part has different shrinkage ratios in three main directions, namely, the flow direction, perpendicular to the flow direction, and the direction through the thickness. The results of the analysis of variance showed that the cooling time is the most influential parameter on both the shrinkage (except in thickness) and warpage. The shrinkage in the flow direction as well as in perpendicular to the flow direction decreased with increasing the cooling time. Warpage also decreased with increasing the cooling time. Injection pressure and melt temperature were found to be effective on shrinkage in thickness. Effects of mould temperature, packing pressure, and packing time were found to be limited. A statistically significant relationship has been noticed among shrinkage, warpage, and residual stresses during the study.

Predicting Human Discretion to Adjust Algorithmic Prescription: A Large-Scale Field Experiment in Warehouse Operations

Conventional optimization algorithms that prescribe order packing instructions (which items to pack in which sequence in which box) focus on box volume utilization yet tend to overlook human behavioral deviations. We observe that packing workers at the warehouses of the Alibaba Group deviate from algorithmic prescriptions for 5.8% of packages, and these deviations increase packing time and reduce operational efficiency. We posit two mechanisms and demonstrate that they result in two types of deviations: (1) information deviations stem from workers having more information and in turn better solutions than the algorithm; and (2) complexity deviations result from workers’ aversion, inability, or discretion to precisely implement algorithmic prescriptions. We propose a new “human-centric bin packing algorithm” that anticipates and incorporates human deviations to reduce deviations and improve performance. It predicts when workers are more likely to switch to larger boxes using machine learning techniques and then proactively adjusts the algorithmic prescriptions of those “targeted packages.” We conducted a large-scale randomized field experiment with the Alibaba Group. Orders were randomly assigned to either the new algorithm (treatment group) or Alibaba’s original algorithm (control group). Our field experiment results show that our new algorithm lowers the rate of switching to larger boxes from 29.5% to 23.8% for targeted packages and reduces the average packing time of targeted packages by 4.5%. This idea of incorporating human deviations to improve optimization algorithms could also be generalized to other processes in logistics and operations. This paper was accepted by Charles Corbett, operations management.

Experimental And Numerical Studies of Shrinkage and Sink Marks On Injection Molded Polymer Gears

Injection molding is an efficient and most economical process employed for the mass production of plastic gears and helps to reduce the processing time and cost required to produce the desired geometry. However, significant process and product qualification of plastic gears face the shrinkage and sink marks issues during cooling and after ejection. In present work, the best gate locations and flow resistance analysis along with a polypropylene (PP) were carried out using Autodesk Moldflow Insight 2019.05. The numerical and experimental study was conducted to evaluate the effect of packing pressure, packing time, and melt temperature on diametric shrinkage, mass, and sink marks of PP gear. The results show that by increasing packing pressure and packing time, the diametric shrinkage decreased but mass increased. However, as the melt temperature increased the diametric shrinkage also increased but the mass decreased. The minimum diametric shrinkage of 0.562% was found in numerical analysis and 1.619% found in an experimental analysis at the same injection molding process parameters. Mostly, the sink marks were observed in the gear surface between hub and dedendum circle.

USULAN PENERAPAN LEAN SIX SIGMA UNTUK MENINGKATKAN KUALITAS PRODUK SEMEN

Penelitian ini dilakukan di sebuah perusahaan yang bergerak di bidang packing plant. Proses pada packing plant tersebut tentunya tidak terlepas dari permasalahan pemborosan yang menjadi kendala saat pengepakan semen berlangsung. Tujuan dari penelitian ini adalah untuk mengidentifikasi jenis-jenis pemborosan, mengidentifikasi akar penyebab pemborosan, mengeliminasi pemborosan dan memberikan usulan tindakan perbaikan dengan menerapkan Lean Six Sigma. Lean Six Sigma merupakan sebuah metode yang digunakan untuk mengeliminasi pemborosan yang terdapat pada lantai produksi serta mengidentifikasi penyebab kecacatan produk dengan pendekatan DMAIC (Define, Measure, Analysis, Control). Hasil penelitian menunjukkan jenis pemborosan yang paling berpengaruh adalah defect product, waktu pengepakan yang melebihi batas toleransi (OTIFIC), antrian, unnecessary motion, over processing, transportasi dan penumpukkan. Akar penyebab terjadinya pemborosan adalah karena kurangnya keterampilan, kurang teliti dan kelelahan, kondisi peralatan mulai aus serta kurangnya pemeliharaan pada peralatan yang digunakan, SOP kerja yang kurang tepat dan mendetail, alur transportasi yang bolak-balik karena tata letak yang tidak tepat. Aktivitas yang merupakan pemborosan dan harus dieliminasi adalah saat operator packer kedua menghitung ulang jumlah bag. Dari hasil penelitian didapatkan beberapa usulan perbaikan yakni dengan memperbaiki SOP kerja yang ada, menerapkan program 6S, membuat SOP 6S, melakukan pelatihan kerja, membuat standar kriteria khusus dalam proses perekrutan karyawan, membuat label atau tanda pada tiap tumpukkan bag, melakukan pemeliharaan secara rutin dan berkala, melakukan pengawasan terhadap kinerja karyawan serta membuat peraturan baru untuk mendisiplinkan karyawan. AbstractThis research was conducted in a company engaged in the packing plant. The process of packing plant is certainly not separated from the problem of waste that become an obstacle when packing cement in progress. The purpose of the study was to identify the types of waste, identify the root cause of waste, eliminate waste and provide proposed corrective action by implementing Lean Six Sigma. Lean Six Sigma is a method used to eliminate waste on the production floor and identify the cause of product defects with the approach of DMAIC (Define, Measure, Analysis, Control). The results showed the most influential types of waste are defect product, packing time exceeding the tolerance limit (OTIFIC), queuing, unnecessary motion over processing, transportation and stacking. The root cause of waste is due to lack of skills, less through and fatigue, equipment condition began to wear and lack of maintenance on the equipment used, work SOP that is less precise and detailed, the flow of transportation commute due to improper layout. Activity that is a waste and should be eliminated is when the second packer operator recalculates the number of bags. From the research results obtained several proposed improvements namely by improving the existing work SOP, implementing the program 6S, creating SOP 6S, conducting work training, creating special criteria standards in the recruitment process, creating labels or marks in each bag, conduct regular and periodic maintenance, supervise the performance of employees and make new regulations to discipline employees.Keywords: DMAIC; Lean Six Sigma; Product Quality; Waste

Experimental and Numerical Study Determining the Warpage Phenomenon of Thin-Wall Injection Molding

This study emphasizes the warpage phenomenon of thin-walled parts using acrylonitrile-butadiene styrene (ABS) plus polycarbonate (PC) plastics for optimal processing by thin-wall injection molding. The authors first employed the Moldflow software to analyze the runner’s balance on multicavities for thin-walled parts and to simulate the warpage of thin-walled parts with thin-wall injection molding. Then, this study used those data to fabricate a real mold by computer numerical control machining. For this study, the authors fabricated thin-walled parts and measured their warpage using various process parameters (injection speed, injection pressure, mold temperature, packing time, and melt temperature) with thin-walled injection molding. Finally, the authors found that the most important processing parameter was the packing time for warpage phenomenon of thin-walled parts by thin-wall injection molding.

The simulation of the warpage rule of the thin-walled part of polypropylene composite based on the coupling effect of mold deformation and injection molding process

Aiming at the problem that a thin-walled plastic part easily produces warpage, an orthogonal experimental method was used for multiparameter coupling analysis, with mold structure parameters and injection molding process parameters considered synthetically. The plastic part deformation under different experiment schemes was comparatively studied, and the key factors affecting the plastic part warpage were analyzed. Then the injection molding process was optimized. The results showed that the important order of the influence factors for the plastic part warpage was packing pressure, packing time, cooling plan, mold temperature, and melt temperature. Among them, packing pressure was the most significant factor. The optimal injection molding process schemes reducing the plastic part warpage were melt temperature (260°C), mold temperature (60°C), packing pressure (150 MPa), packing time (2 s), and cooling plan 3. In this situation, the forming plate flatness was better.

Development of an Integrated Melt Modulation System to Manipulate Cold-Runner Injection Molding Processing Parameters and Their Effects on Final Product Physical and Optical Properties

Packing processing parameters, including packing pressure and packing time, have significant impact on the internal molecular orientations, mechanical properties and optical performance of injection molded polymeric products. One of the limitations of cold-runner injection molding machines is the lack of real-time control of packing processing parameters during an injection molding cycle. As a result, a new melt modulation device has been developed and experimentally validated to control melt flow and manipulate processing parameters during cold-runner manufacturing. The use of the integrated melt modulation device has shown enhancement of physical properties and optical performance of injection molded polymeric products. Numerical simulations and experimental results of common thermoplastic optical polymers, such as PMMA, PC, and GPPS have been conducted and briefly demonstrated herein.

Improvement of ADC12 Alloy by Optimizing CSP Process Parameters via Multiple Nonlinear Regression Analysis

In order to improve the quality of ADC12 alloy billets prepared by Chips Solid Pressing (CSP) process, the effects of pressing temperature, pressure and packing time on the density of ADC12 alloy billets were investigated by using the orthogonal array and multiple nonlinear regression analysis. The results indicated that the pressing temperature has the greatest effect on the density of the billets, and it is followed by pressing pressure and packing time. The optimized process parameters, including a pressing temperature of 250oC, pressing pressure of 640MPa and packing time of 45 seconds, can be used to obtain the most compact billets of ADC12 alloy prepared by CSP process.

Influence of Processing Conditions on the Morphological Structure and Ductility of Water-Foamed Injection Molded PP/LDPE Blended Parts

Water-foamed injection molding (WFIM) uses conventional injection molding (CIM) with water as a physical foaming agent. Compared to CIM, WFIM is a much more complicated process. As such, it is critical to determine the processing conditions for fabricating quality parts using WFIM. We used the design of experiment (DOE) method based on the Taguchi method to determine the influence of the processing conditions on the morphological structure and ductility of PP/LDPE WFIM parts, which were investigated by tensile testing and scanning electron microscopy (SEM). Our research suggests that fabricating PP/LDPE super-ductile parts using WFIM is indeed feasible. Our research also indicates that there is a close relationship between the ductility and the foamed structures, both of which are deeply influenced by the processing conditions. The analysis of variance results shows further that the water content had the greatest influence on the ductility, followed by the melt temperature, packing time, packing pressure, and PP/LDPE ratio. However, the ductility was only slightly influenced by the mold temperature, injection pressure, and injection time in WFIM. As to the number of cells, the order of influence was melt temperature, water content, packing time, packing pressure, mold temperature, injection pressure, PP/LDPE ratio, and injection time, in that order. In addition, applying DOE is a quite effective method for deducing the optimal set of effective factors in WFIM to produce super-ductile parts with a maximum number of cells. To our knowledge, this is the first time that the relationship among the processing conditions, ductility, and foamed structure of PP/LDPE WFIM super-ductile parts has been investigated and reported.