Micro Injection Molding

1.1	Introduction

The present chapter introduces the design of micro molding machines from two different perspectives: analysis of patents on the technology, and design architectures and solutions for the micro injection molding machines.

The first analysis is oriented to provide a quantitative scenario on the attempts to exploit research for commercial uses, and it is performed taking into account patents applications worldwide. It helps in situating the micro injection molding domain in the industrial market (particularly on the machine manufacturing side). Conversely, the second part of the present chapter focuses on some relevant architecture aspects of micro injection molding machines that have been analyzed from a functional perspective. The choice of the machines is based on interesting architectures that have been the target of various researches in the recent past and that are often cited within the present book.

1.2	Patent Analysis

Patents data can provide an overview of the main technologies related to an artifact. A landscape study of the patents concerning micro injection molding machines and their components has been performed. Such study identified a patent set selected from a patent database provided by Erre Quadro s. r.l. (http://www.errequadrosrl.com/).

The patent set contains 2809 individual patents. They cover a period of 135 years and have been filed by more than 500 assignees coming from 17 countries. Many of them (>75%) belong to the last two decades, when patents and their use increased thanks to the internet adoption and patent spread.

Different analyses have been carried out on the selected patent set.

First, a linguistic analysis has been performed to identify expressions (i. e., multi-word terms) that are specific to the particular patent set. Figure 1.1 illustrates the most relevant expressions used in the patent set on micro injection molding machines. The size of the expressions within the tag cloud is proportional to their frequency of occurrence in the selected patent set.

The tag cloud reports many of the components of the machines and a particular interest in the mold cavity as a key element in the specific case of micro injected components.

Patents filed in states that are members of the World Intellectual Property Organization (WIPO) are assigned, by the patent office, to one or more IPC 1 classes. Thus, each IPC class can be interpreted as a corresponding technological area. Table 1.1 provides a list of the 10 largest IPC classes within the investigated set of patents. As expected, the main topics are those related to techniques for “working plastic” and “organic macromolecular compounds” of various origins.

Figure 1.2 shows how patents are distributed in time according to filing date. Referring to such figure, the distribution shows a growing trend (more regular with respect to other machines and disciplines) but with several fluctuations and some anomalies (e. g., the year 2000).

An important remark concerning Figure 1.2: patents become accessible to the public only after publication, which on average takes place about 18 months after a patent has been filed. During this period patents undergo examination by a patent office. This may explain, at least in part, the noticeable drop that can be seen in the last two years.

Some of the most important information that can be extracted from patents meta-data is related to the companies that own the property of the patents, i. e., the assignees. The top 10 assignees found in the patent set are shown in Table 1.2.

The values of the percentages of patents owned by each assignee show that the patent ownership is rather spread and there is not a big player that has a remarkable fraction of patents. However, Nissei Plastic Ind. Company is the most relevant, followed by Toshiba Mach. Company and Sumitomo Heavy Industries. Such distribution is typical of innovative products built on the basis of pre-existing technologies and where innovation and disruption happen mainly within the companies’ R & D division.

Additional interesting information concerns where the assignees of the patents are located (such data are different from the headquarters of multinational companies but often refer to the plant or division where the invention has been conceived and tested). However, before presenting the geographical distribution, it is important to notice that assignees can be further distinguished in two categories: public and private. Public assignees are institutions or organizations like universities and research centers. Private assignees are companies and individuals.

Figure 1.3 and Figure 1.4 show the concentration of private and public assignees, respectively. The different colors in the images represent the different concentrations of assignees. Therefore, in Figure 1.3 the light blue areas represent a smaller number of private assignees than the dark blue regions. Similarly, in Figure 1.4, the red areas reveal the countries where a high number of public assignees filed patents, with respect to the green ones.

The analysis reveals that the highest concentration of private assignees—in terms...