Vol.60 No.1 (2017)

At this site technical articles published at the YOKOGAWA technical report are introduced.

Co-innovative R&D with Customers

Marketing-driven Research and Development

  • Tsuyoshi Abe, PhD*1

*1 : Vice President, Head of Marketing Headquarters

Co-innovation with Customers in Research and Development

  • Tsuyoshi Yakihara*1
  • Satoshi Kato*2

*1 : Innovation Center, Marketing Headquarters
*2 : Research and Development Division, Innovation Center, Marketing Headquarters

   The intention behind Yokogawa’s corporate brand slogan, “Co-innovating new value with customers,” is also reflected in the activities of the R&D Division. The R&D Division is committed to conducting R&D and developing co-innovations in partnership with customers. This paper explains how we address these tasks. Specifically, innovation comprises three stages, and we define research themes targeting the three fields of biotechnology, materials, and energy, then carry out R&D. We aim to create new value while identifying actual needs and solving customers’ problems.

Development of a Nucleic Acid Detection System for Rapid Microbial Tests

  • Takashi Tadenuma*1
  • Tomoyuki Taguchi*1

*1 : Research and Development Division, Innovation Center, Marketing Headquarters

   Food safety is one of the most important issues for the food industry. Although the detection of microbial contamination is indispensable for the management of food hygiene, conventional cultural enrichment methods require from days to weeks to obtain results. Thus, there is an increasing need for rapid detection technology to shorten the examination time. We have developed signaling array technology for detecting nucleic acids with a sensing probe, which hybridizes with specific nucleic acids and emits fluorescence. This probe enables conventional DNA microarrays used for microbial tests to offer one-step detection of unlabeled nucleic acid fragments, thus simplifying the detection of microbes. This paper describes details of this signaling array technology and its applications.

Development of Polarization Imaging Sensing Technology for Controlling the Quality of Printed Electronics Manufacturing

  • Kodai Murayama*1
  • Tomohito Nohno*1
  • Soukichi Funazaki*1
  • Daisuke Kumaki*2
  • Shizuo Tokito*2

*1 : Research and Development Division, Innovation Center, Marketing Headquarters
*2 : Organic Electronics Research Center, Yamagata University

   Printed electronics has manufacturing advantages such as low environmental load and low cost in addition to the characteristics of the device itself such as flexibility and transparency, which cannot be achieved in conventional semiconductor devices. As research and development on printed electronics increases, there are high expectations for Roll-to-Roll (R2R) production in which devices are made on a film using coating and printing technology. In order to continuously produce devices on the film which is being rolled up in R2R production, non-contact, high-speed sensing equipment is required.Through collaborative research with Yamagata University, we found that the crystallinity of the organic semiconductor layer is crucial for securing device quality, and we developed polarization in- line sensing technology that can visualize the crystallinity of the organic semiconductor layer in-line for achieving R2R production.

Development of an Electric Field Sensor Using the Electro-optic Effect

  • Jun Katsuyama*1
  • Yoshinori Matsumoto*1
  • Hiroyuki Sugino*1
  • Hiroaki Tanaka*1

*1 : Research and Development Division, Innovation Center, Marketing Headquarters

   Metal antennas are generally used for measuring electric field strength. However, it is difficult to precisely measure the electric field of a source with extremely low voltage because the antenna itself disturbs the electric field. To solve this problem, we have developed an electric field sensor with low disturbance and excellent frequency characteristics by using an electro-optic crystal for an antenna, and non-contact voltage measurement technology that uses this sensor. In contrast to conventional electro-optic sensors with the sensitivity of several megahertz in the low- frequency range, the new sensor extends the measuring band to about 20 Hz by suppressing the electric conduction effect in the optical crystal. This paper shows the results of non-contact voltage measurement of photovoltaic cells, and also reports the EMC measurement of electronic equipment and the non-contact observation of signal wave patterns of circuit boards as application examples.

Efficient Field Communication with Augmented Reality

  • Yasuki Sakurai*1
  • Yosuke Ishii*1

*1 : Incubation Division, Innovation Center, Marketing Headquarters

   A shortage of skilled operators has been a major problem in plant operation for many years, hindering stable operation and raising the risk of serious accidents. Although there is an urgent need to train young workers and hand on skills, there is also a shortage of skilled operators who can lead such work, making it difficult to secure work-ready operators. This is a vicious circle for customers. To overcome this problem, Yokogawa has been developing a real-time visual sharing system using augmented reality (AR) technology. This solution is expected to facilitate handing on skills while overcoming the shortage of skilled operators. Yokogawa has been conducting and evaluating a series of proof of concepts (PoC). This paper reports the concept and development of this solution, and describes our survey of customers’ needs and challenges by using a prototype.

Technology for Estimating the Battery State and a Solution for the Efficient Operation of Battery Energy Storage Systems

  • Soichiro Torai*1
  • Masahiro Kazumi*1

*1 : Incubation Division, Innovation Center, Marketing Headquarters

   Expectations for a distributed energy system including renewable energy are increasing worldwide, and stationary battery energy storage systems are indispensable for securing peak-shifting of power demand and stable operation. For the efficient operation of these systems, it is crucial to identify battery conditions such as the state of charge and degradation and to make full use of battery pack capacity. This paper describes Yokogawa’s solution for the efficient operation of battery energy storage systems. The technology for identifying the battery state is based on our original model of battery characteristics.

Development of Glassless All-solid-state pH Sensor

  • Yukihiro Shintani*1
  • Kotaro Ogawa*1
  • Toshiyuki Saruya*1
  • Hiroshi Kawarada*2

*1 : Research and Development Division, Innovation Center, Marketing Headquarters
*2 : Faculty of Science and Engineering, Waseda University

   Glass electrode pH meters are the de-facto standard for measuring pH and Yokogawa offers pH meters of this type, which are widely used by many customers in various industries including chemicals, water and sewerage, petrochemicals, and biotechnology. However, glass electrode pH meters involve inherent risks: glass is fragile and the internal liquid may leak and contaminate samples. Therefore, we have been working with Waseda University to develop a next- generation all-solid-state pH sensor. This paper describes the key technologies and reports the characteristics of a prototype.

Machine Learning Applied to Sensor Data Analysis: Part 2

  • Hiroaki Kanokogi*1
  • Go Takami*1

*1 : Field Digital Innovation Division, New Field Development Center, IA Product & Service Business Headquarters

   In recent years, new technologies of machine learning and artificial intelligence (AI) have been progressing rapidly. Although there are high expectations for their application to industrial automation, there are various misunderstandings. For instance, some people incorrectly believe that AI will immediately deliver something new, but it is necessary to choose a suitable method to solve problems. Meanwhile, the pessimistic opinion that AI is eventually useless is also incorrect, as evidenced by impressive results in particular fields such as image recognition and board games. After all, what can machine learning actually do? This paper explains the characteristics of machine learning with examples of how Yokogawa uses it in plant data analysis.

Development of High-resolution Silicon Resonant Atmospheric Pressure Sensor

  • Ryuichiro Noda*1
  • Yusuke Matsuo*1
  • Tetsuya Watanabe*1
  • Takashi Yoshida*1

*1 : Semiconductor Application Development Center, IA Products & Service Business Headquarters

   There is an increasing need for high-accuracy, high-resolution atmospheric pressure sensors in the fields of the Internet of Things (IoT) and environmental measurement. Concerning the IoT, atmospheric pressure sensors are used as an altimeter or barometer, while for environmental measurement they are used as a barometer to detect extremely small and low-frequency pressure fluctuations, called infrasound, which are caused by earthquakes and tsunamis. Yokogawa has been offering silicon resonant pressure sensors since the 1980s, and its DPharp series differential pressure/pressure transmitters are widely used by many customers. In response to the increasing demand, Yokogawa decided to apply the technologies of silicon resonant sensors to the development of new atmospheric pressure sensors. This paper describes a prototype which achieves a high accuracy of 2.5 Pa and a high resolution of 0.1 Pa, equivalent to the accuracy of existing pressure standards.

High-sensitivity Silicon Resonant Strain Sensor

  • Takeru Samejima*1
  • Yoshitaka Suzuki*1
  • Nobuyuki Hamamatsu*1
  • Hiroshi Yokouchi*1
  • Takashi Yoshida*1

*1 : Semiconductor Application Development Center, IA Products & Service Business Headquarters

   Silicon resonant sensors, which are used in the DPharp series differential pressure transmitter, calculate pressure by measuring the strain of a diaphragm caused by the pressure with a built-in silicon resonant strain gauge. Although this gauge features higher sensitivity than metal foil strain gauges or piezo-resistance type strain gauges, measurement error is caused by temperature when its coefficient of thermal expansion is different from that of objects to be measured. To solve this, we have developed a new sensor by mounting a silicon resonant sensor on a thermal stress compensation structure and by driving the gauge electrostatically, achieving high sensitivity and less power consumption. This sensor delivers excellent affinity with wireless measurement and the Industrial Internet of Things (IIoT).

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