Sushi Sensor For Industrial IoT Solution Achieves . - Yokogawa
Sushi Sensor for Industrial IoT Solution Achieves “Sensemaking”Sushi Sensor for Industrial IoTSolution Achieves “Sensemaking”Akirou Kitajima *1Takayuki Sugizaki *1In terms of Yokogawa’s digital transformation (“DX”), digitization that shows how tocollect and integrate data, and digitalization that shows how to use data effectively, can helpcustomers accelerate continuous value creation and transform their business operations.This paper explains the importance of “sensing” (collecting data) and “sensemaking”(adding value to data) at each step of DX and introduces “Sushi Sensor” as a solution forsolving customers’ equipment maintenance issues. The paper also outlines benefits tocustomers through specific examples of using Sushi Sensor. “Sensing” and “sensemaking”using Sushi Sensor can improve not only the efficiency of equipment maintenance but alsoproduct quality by integrating equipment data with operating data, thus achieving DX andultimately transforming the entire plant, within and between plants and the entire company.INTRODUCTIONPlant managers are responsible for improving productionefficiency in a rapidly changing business environmentwhile maintaining aging equipment. Maintaining the highavailability and reliability of plant equipment while improvingthe operational performance is a key to continuing business.Moreover, as innovative digital technologies such asartificial intelligence (AI), Industrial Internet of Things (IIoT),and big data have emerged in recent years, an increasingnumber of customers want to introduce these new digitaltechnologies to improve productivity.Production process data obtained by using operation*1 CX Business Strategy Department,Information Technology Center,IA Products and Service Business Headquarters7technology (OT) have been used for improving the productivityof plants. Equipment data obtained f rom infor mationtechnology (IT) are increasingly used for improving theefficiency of equipment maintenance. By uniting these data,innovative digital technologies have the potential to createnew plant value.Synaptic Business Automation is Yokogawa’s industrialautomation (IA) business concept (1). Based on this, we areworking hard to improve customers’ productivity by achievingDX, which makes the most of digital technology and helpscustomers digitize their business.Meanwhile, Yokogawa has accumulated business anddomain knowledge through various OT projects in plantsand acquired practical know-how. This enables us to satisfycustomer requests by offering wireless solutions combinedwith IIoT sensors. Yokogawa’s Sushi Sensor is one such sensorthat provides wireless solutions which are clearly differentiatedin the plant field.Yokogawa Technical Report English Edition Vol.62 No.2 (2019)61
Sushi Sensor for Industrial IoT Solution Achieves “Sensemaking”Yokogawa released the first Sushi Sensor, a wirelessvibration sensor, in March 2018. In July 2019, Yokogawareleased wireless temperature and pressure sensors, expandingthe sensor portfolio (Note 1: The wireless vibration sensor hasbeen released in Japan and some other countries. Althoughthe wireless pressure and temperature sensors are currentlyavailable only in Japan, these are due to be released overseas).This paper introduces Sushi Sensor, which is a solution for theIIoT that revolutionizes the two main DX steps of “sensing”and “sensemaking” and shows an approach to Yokogawa’sideal DX.YOKOGAWA’S IDEAL DXYokogawa’s ideal DX is achieved with three steps:digitization (digitization of information), digitalization(digitization of processes), and digital transformation of thewhole corporate activity and culture.DigitizationDigitization means digitizing information. Informationvisually recognized or recorded on paper is coded with 0 and1 and electronically recorded as digital information so thatcomputers can process it easily. Digitization facilitates dataprocessing.Digitization is the first step of DX in plant operation andequipment maintenance, and it is achieved by automating thedata acquisition process that had been performed manually.Conventionally, data in a plant are collected from sensors viawired or wireless sensor networks. This is called “sensing.”Sensing is widely used for measuring the parameters ofproduction processes and the important data of equipment.However, not all of the data required by customers areobtained; equipment for which real-time monitoring is notrequired and those at distant locations are not connected tosensor networks. These are usually monitored by an operator’sround checks.The number of targets to be monitored is increasingas equipment is aging. Meanwhile, the number of workersavailable for operator rounds is decreasing due to theretirement of skilled workers and other reasons. Moreover,it costs much to collect measurement data from equipmentthat is difficult to access during operator rounds, for example,those located at height or in hazardous areas. However,collecting data in the field is increasingly important toimprove production efficiency and product quality. To achievedigitization, it is necessary to deploy a huge number of sensorsin a plant and operate them in a cost-effective manner.DigitalizationDigitalization means digitizing the process of identifyingany significant matter in digitized data and creating value.Collecting data is not customers’ goal; they want to obtainvalue or benefit from the data. For example, they want to detectany signs of abnormality of equipment early by monitoringthe trend of data; they also want to predict failure or diagnosea malfunction by using AI and machine learning to analyzedata. They expect new value to be created from data.Conventionally, the task of value creation was left to skilledworkers who applied their intuition and experience to deliveraccurate judgments. However, more and more skilled workersare retiring even as the number of points to be monitored isincreasing. Some countermeasures are needed to overcomethis situation. Moreover, there are still large amounts ofequipment data that have not yet been digitized. Thesemay bring value radically different from the existing value.Yokogawa calls this step of digitalization “sensemaking” (2).Sensemaking facilitates the creation of signif icantvalue from data and has an important role in achieving DX.Currently, it is not easy for customers to understand andanalyze the meaning of data and determine how to implementthem in daily operation. In other words, many vendors providecustomers with tools for digitization, but they have notsuccessfully offered tools for digitalization to make full useof plant data. Vendors should offer a solution that facilitatesthe shift from sensing to sensemaking. Such a solutionhas a crucial role in achieving maintenance with digitizedequipment data.Figure 1 shows the shift in sensors’ role from sensing tosensemaking (2).Key factors for the success of sensemaking are intelligentFigure 1 Role of sensor: The shift from sensing to sensemaking62Yokogawa Technical Report English Edition Vol.62 No.2 (2019)8
Sushi Sensor for Industrial IoT Solution Achieves “Sensemaking”Figure 2 OODA loop that achieves sensemakingsensing and advanced data analysis based on business anddomain knowledge. Intelligent sensing means flexible, scalablesensing with excellent connectivity and environmentalresistance such as explosionproof. Sensemaking is notachieved by the PDCA cycle, which is a conventionalcontinual improvement method over a long period, but bythe OODA loop, which is a continuous thinking method ofrepeating quick observation, judgment, decision-making andexecution over a short period. Figure 2 shows the OODA loopthat achieves sensemaking (2). This loop effectively carriesout the cycle of Observe (observation), Orient (judgement ofconditions), Decide (decision-making), and Act (execution).In this loop, sensing assumes the role of observation throughintelligent sensing while sensemaking is responsible forjudgement of conditions through advanced data analysis andquick decisions in real time. Then, human workers take actionfor creating value and the loop then returns to observation.This loop works effectively in an environment that has muchvariability, uncertainty, complexity, and ambiguity.Digital TransformationThe final step of DX aims to improve the operationalperformance of plants and promote the continuation ofbusiness. It transforms the whole corporate activity andculture digitally. In other words, it totally changes how acompany, business, and people behave. Although valuecan be extracted by sensing and sensemaking, it is usuallydiscussed in independent OT and IT fields. These includethe operation of production processes by OT and equipmentmaintenance and energy management by IT. In this final stepof DX, epoch-making value can be created by unifying thefunctions and data of OT and IT. For example, for optimizingthe parameters of a production process, data on both theequipment state and performance information are digitizedand fed back to the production process. This can increase theefficiency of production and the quality of products. Yokogawahas accumulated the domain knowledge of business and a9production process in plant operation as well as OT and ITsensing technologies. By using AI/machine learning foradvanced analysis, we can help customers proceed with digitaltransformation.Through these three steps of DX, we can help customersimprove profitability and sustainable growth.CUSTOMERS’ CHALLENGES AND THEIRSOLUTIONSA major concer n of plant managers is unexpectedshutdown due to any failure of plant equipment, which caneasily cause losses worth hundreds of millions of yen in asingle year. Moreover, the aging and shortage of the workforcegreatly affect production and equipment maintenancework. Capital that can be spent on maintenance is limited,for example, to 1 to 2% of profits (1). Plant managers havea responsibility to improve productivity and safety, offereducation and training to workers, and secure workers whilereducing operation cost.The following sections describe customers’ challengesand Yokogawa’s solutions regardi ng plant equipmentmaintenance, along with the following three steps of DX.Challenges for Digitization and Their SolutionsFor digitization, sensing must overcome the followingchallenges. Can measure a broad range of physical quantities ofequipment with high quality and reliability. Can digitize sensing data and place them online to drivethe overall health and performance of equipment. Can be deployed and operated easily. Have enough environmental resistance to keep operating ina severe environment for a long time.Yokogawa offers the following solutions to thesechallenges. Measurement of various physical quantities (vibration,temperature, pressure)Yokogawa Technical Report English Edition Vol.62 No.2 (2019)63
Sushi Sensor for Industrial IoT Solution Achieves “Sensemaking” Compact, lightweight with integral wireless and measurementfunctions Low power consumption and long-distance wirelesscommunication Dustproof, waterproof, and explosionproofChallenges for Digitalization and Their SolutionsFor digitalization, sensemaking must overcome thefollowing challenges. Can perform advanced data analysis. Can monitor the trend to effectively use measured data forequipment maintenance. Can detect signs of abnormality before equipment failureand can perform failure diagnosis. Have a system for equipment maintenance with excellentcost-effectiveness.Yokogawa offers the following solutions to thesechallenges. Data-analysis type diagnosis and decision-making by usingAI/machine learning Cloud environment that can store various data for analysisChallenges for Digital Transformation and Its SolutionThe customer challenge in the final step of DX is tosecure a cloud environment that can save and unite productionprocess data and equipment data. This environment is alsorequired to have functions that can combine both types ofdata in a mutually complementary manner, analyze them,determine the action to take, and feed the results of theanalysis back to the production site.Business and domain knowledge has an important roleto play in the solution. Yokogawa has accumulated technicalknowledge in the production process industry over manyyears. In addition, through partnerships with customers,Yokogawa helps customers transform their business processand digitalize their management. With this solution, Yokogawacan offer promising and continuous business results.ENABLING TECHNOLOGY (3)Among the solutions offered by Yokogawa, this sectionfocuses on Sushi Sensor, a wireless solution for the IIoT. SushiSensor follows the trend from digitization to digitalization andachieves the shift from sensing to sensemaking.Sushi SensorYokogawa can help customers digitize the sensing data inplants and place them online by introducing Sushi Sensor. Itsfeatures are as follows.(1) Easy installationSushi Sensor uses the LoRaWAN communication standard.LoRaWAN is one of the low power wide area (LPWA)network protocols, which are now attracting attention asa wireless communication system for the IoT (for sensordevices). LoRaWAN is an open communication standardpromoted by the LoRa Alliance of more than 500 IoT64companies and users worldwide. Even in a plant packedwith various equipment, this protocol ensures long-distancecommunication 1 km away from sensors to a gateway evenin the “pipe jungle” of plants as long as the sensors andthe gateway are located outdoors and are not surroundedby metal or concrete structures. LoRaWAN-compliancedevices can be installed and operated easily without havingto design wireless routes and install repeaters. Figure 3shows a plant layout example with Sushi Sensor.Easy to relocateEasy to addEnsures long-distancecommunication up to 1 kmeven in a plant packedwith various equipment.Figure 3 Example of plant layout with Sushi Sensor(easy installation)Moreover, Sushi Sensor is battery-powered. The batterycan be easily replaced and there is no need for wiringwork. When the data update cycle is set to 1 hour, thewireless vibration sensor can operate for four years, andthe wireless pressure sensor and the wireless temperaturesensor for 10 years (depending on temperature conditions).The wireless vibration sensor can be easily fixed withscrews or a magnet (optional).(2) Environmental resistanceSushi Sensor satisfies the basic challenges for a harsh plantenvironment: dustproof and waterproof (IP66/67), andexplosionproof.(3) Wide varietyFollow i ng t he XS770A w i reless v ibr at ion sen sor,Yokogawa released the XS530 pressure measurementmodule, the XS550 temperature measurement module,and the XS110A wireless communication module witha built-in battery. The pressure and temperature sensorsconsist of a measuring module and the XS110A wirelesscommunication module. The XS110A can be assembled toany measuring module. By replacing a measuring module,Sushi Sensor can measure various physical quantities.Taking advantage of this feature, Yokogawa is trying togrow the lineup of measuring modules and is expandingthe portfolio of the Sushi Sensor.(a) XS770A wireless vibration sensorThe XS770A wireless vibration sensor is fixed to the targetequipment with M6 screws or a magnet (optional). In the caseof magnet mounting, the measurement location can be easilychanged. This feature is useful for temporary measurement.Yokogawa Technical Report English Edition Vol.62 No.2 (2019)10
Sushi Sensor for Industrial IoT Solution Achieves “Sensemaking”(b) XS530 pressure measurement moduleThe XS530 pressure measurement module is screweddirectly into piping. The XS530, connected with theXS110A, can substitute a pressure gauge that is widelyused in many plants and can place data online.(c) XS550 temperature measurement moduleAlthough the XS770A wireless vibration sensor canmeasure the surface temperature of the target equipment,sometimes it is necessary to measure a wider temperaturerange and the temperature inside piping. To satisfy theseneeds, Yokogawa developed the XS550 temperaturemeasurement module. This module, connected with theXS110A, operates as a temperature sensor when it iscombined with a thermocouple. The range and accuracy ofmeasurement depend on the type of thermocouple.Previously, maintenance staff performed measurementswith a portable device in operator rounds and wrote down theresults on paper. Replacing these operator rounds or beingadded for these tasks, Sushi Sensor can digitize these dataeven at locations which are difficult for human workers toaccess due to danger or distance. Since Sushi Sensor doesnot depend on workers’ ability and availability, it ensuresuniform quality of measurements and increases the frequencyof inspections. As a result, it helps improve the efficiency ofequipment maintenance, pass down skills that experts haveaccumulated over years, and alleviate the labor shortage.APPLICATION CASEBefore introducing Sushi SensorAfter introducing Sushi SensorCloudFigure 4 Operator rounds replaced withonline monitoring with Sushi SensorCase 2: Detecting an abnormality of a ball bearing with thehelp of AI/machine learningFive months after Sushi Sensor started to monitor rotarymachines in a plant, it detected an unusual rise in accelerationpeak values. This suggested that bearing wear had reachedthe final phase. When AI/machine learning was applied tothe measurement data, it revealed that signs of abnormalityhad been detected three months before the failure as shownin Figure 5. This means that the combination of Sushi Sensorand AI/machine learning is useful for detecting signs ofabnormality of ball bearings early, which is a cause of failureof rotary machines. This is a good example of sensemaking inwhich new value is created from digitized sensing data withthe help of advanced analysis by AI/machine learning.This section shows how to use Sushi Sensor for achievingthe shift “from sensing to sensemaking” in the OODA(observe, orient, decide, and act) loop.Wireless Vibration SensorCase 1: Reducing the cost of operator roundsA customer had outsourced the task of measuring thevibration at 200 rotary machines in a chemical plant, and thecontract staff performed operator rounds and recorded theresults manually. Since these non-digitized data only showedthe equipment condition at the time of inspections, their usagewas limited and the trend of the vibration condition couldnot be monitored. Therefore, equipment maintenance wasperformed as time-based maintenance (TBM), and as a resultof this strategy, the plant was shut down, parts were replaced,and equipment was repaired at periodic maintenance intervals.The introduction of Sushi Sensor made it possible to monitorequipment conditions in real time and online. An alert issuedin real time enables operators to take actions quickly forany abnormality. As a result, the maintenance strategy waschanged to condition-based maintenance (CBM). TBM isa kind of PDCA cycle (long-term continual improvementmethod) while CBM is an OODA loop (continuous thinkingmethod of short-term observation, judgment, decision-makingand execution). Figure 4 shows how operator rounds werereplaced with online monitoring with Sushi Sensor.11Figure 5 Advanced predictive maintenance withSushi Sensor and AIWireless Pressure SensorCase 1: D etecting leaks and clogging of dust collectors andtheir pipingWhen leaks or clogging occur, dust collectors and theirpiping will break down, decreasing the operational efficiencyof a plant. Pressure gauges are conventionally mounted todetect such abnormalities, and visual observation is performedduring operator rounds. However, when measurement pointsare distributed across a wide area, it is difficult to performYokogawa Technical Report English Edition Vol.62 No.2 (2019)65
Sushi Sensor for Industrial IoT Solution Achieves “Sensemaking”multipoint measurement due to the limited availability ofworkers and time. By replacing existing pressure gaugeswith Sushi Sensor or adding Sushi Sensor to these gauges,it is possible to increase the frequency and location ofmeasurement. This also satisfies the demand of customers whowant to acquire all equipment data required for maintenanceand avoids the failure of equipment and the decline inoperational efficiency.Case 2: Pump outputFigure 6 shows an example of online pressure measurement.After driving pumps are switched, for example, from Pump Ato Pump B, operators visually check pressure gauges mountedon the pump to make sure that operation continues as before. Byreplacing these pressure gauges with Sushi Sensor or adding SushiSensor to these gauges and placing the monitoring task online, it ispossible to grasp the operational status of each pump in real timeand improve maintenance efficiency. Since the correlation withthe operational status of other pumps can be grasped in real time,operational efficiency will also improve.Case 2: A dding measurement points to multi-stage heatexchangersI n multi-st age heat exchangers, i nput and out puttemperatures are usually monitored online. However, thisis usually done for the whole system, not each stage. SushiSensor can measure the input and output temperatures, monitorthe trend, and grasp the state of each stage of multi-stage heatexchangers, making it possible to detect an abnormality of anysingle heat exchanger and improve maintenance efficiency.Figure 7 shows an example of monitoring a multi-stage heatexchanger.Measured by a temperature sensorHeatexchangerHeatexchangerPump AMaintenance staff wants tomonitor piping.HeatexchangerPump BMeasured by a temperature sensorPump CFigure 7 Example of monitoring a multi-stageheat exchangerThe output pressure of each pump is measured by a gauge.Gauge pressureXS770APumpFigure 6 Example of online pressure measurementWireless Temperature SensorCase 1: Detecting leaks of safety valvesA safety valve is installed to vent the increased pressureof devices and piping. Under a certain condition, seat leakageoccurs at this valve. In this case, operation must be stoppedimmediately to repair equipment, which greatly affects theproduction. It is also necessary to halt equipment to check forseat leakage visually because the trend cannot be monitoredduring operation. To solve this problem, we focused on thefact that the temperature of the output of the safety valve fallsrapidly when seat leakage occurs. Sushi Sensor can measurethe temperature difference between the input and output of asafety valve and detect the abnormal signs of seat leakage inreal time. It is thus possible to avoid unexpected shutdown andensure stable operation.66OT/IT Complementary Collaboration: StabilizingOperationFinally, a case of digital transformation is shown, inwhich production process data obtained by OT and equipmentdata obtained by IT were combined to complement each otherand product quality was improved.In production equipment, the XS770A wireless vibrationsensor, which had been introduced to monitor the state of therotary machine, revealed a correlation between the operationof this rotary machine and the quality of the product. SushiSensor for monitoring the state and maintaining a suitableoperational condition also served to stabilize the quality ofthe product. This is a good example of digital transformationin which we were able to work together with the customer totransform their business process by using Yokogawa’s sensingtechnology and domain knowledge on the production process.BENEFITS FOR CUSTOMERSCompared with conventional operator rounds, theintroduction of Sushi Sensor makes it possible to increasethe number of measurement opportunities (locations andfrequency) of data that show equipment conditions. Whencustomers appropriately use the acquired data and performsuitable equipment management, they can avoid unexpectedYokogawa Technical Report English Edition Vol.62 No.2 (2019)12
Sushi Sensor for Industrial IoT Solution Achieves “Sensemaking”Figure 8 Yokogawa’s solution based on the integration of OT and ITplant shutdown, improve the maintenance efficiency ofequipment, and minimize plant downtime. As a result, theproductivity of equipment is maximized, and products can beproduced with stable quality as designed. Sushi Sensor cangreatly contribute to not only equipment maintenance but alsomaintaining and improving operational efficiency, securingsafe operation and stability, and maintaining and improvingquality.FUTURE DEVELOPMENT AND NEW VALUECREATIONAchieving DXIn the cloud offered by Yokogawa, it is possible to analyzeproduction process data and equipment data in an integratedmanner, and these integrated data can be used for optimizingproduction. We will analyze the whole business of customersfrom identifying their potential problems to designing andimplementing the optimum solution, executing safe andstable operation, and maintaining and improving productionefficiency. Yokogawa has accumulated strength in the OTdomain. By combining it with the latest IT, we will optimizethe production process, automate and optimize the whole valuechain including the supply chain, reduce risk, and improveefficiency.The data saved and integrated in the cloud can be usednot only for the target plant but also for any plants of thesame kind all over the world. In the cloud, it is possible tocombine real-time production process data that are collectedvia sensor networks and equipment data that are collectedmore frequently than in operator rounds, and it is also possibleto analyze the integrated data precisely. Figure 8 showsYokogawa’s solution based on the integration of OT andIT. Based on business and domain knowledge, productionprocess data obtained from OT are combined in the cloudwith equipment data that are obtained from IT (IIoT data).The data will bring about transformation beyond plants,13i.e. transformation of corporate management, business,and people. This system will ensure high profitability andsustainable growth for customers.Use of AI/machine LearningWith Yokogawa’s cloud environment, customers canintegrate the data across the plant and seamlessly accessthe results of advanced analyses obtained by making fulluse of AI and machine-learning technologies. With the helpof AI/machine learning, equipment abnormalities can bepredicted and the details of failure can be diagnosed. Thediagnostic results facilitate judgment, decision-making, andaction for equipment maintenance. Moreover, integrationwith production process data will provide customers withguidelines on decision-making and actions that lead not onlyto maintenance activity but also product quality.CONCLUSIONThis paper discussed the three steps to achieve DX:digitization, digitalization, and digital transformation.We focused on the shift from sensing to sensemaking andexplained how to achieve sensemaking through intelligentsensing based on business and domain knowledge, advanceddata analysis, and a business method of the OODA loop(observing and judging conditions, making decisions, andtaking action). Furthermore, we showed through severalexamples that Sushi Sensor can facilitate digitizationand digitalization of plant equipment while minimizingmaintenance cost and can secure the reliability and availabilityof equipment. The paper concluded that in the final digitaltransformation step we can help customers to create new valueby taking advantage of our knowledge and experience aboutdomains, and by using production process data that have notbeen fully used for equipment maintenance.If AI, machine learning, and other advanced technologies canbe fully used, it will be possible to create new value and maximizeYokogawa Technical Report English Edition Vol.62 No.2 (2019)67
Sushi Sensor for Industrial IoT Solution Achieves “Sensemaking”the profits of the whole plant. In addition, sharing data via thecloud will make it possible to operate multiple similar plantsefficiently, improve operational efficiency, and promote reforms inthe whole plant, among multiple plants, and in the entire company.REFERENCES(1) Yokogawa Ele ct r ic Cor p., “ Yokogawa’s Sy n apt ic Bu si ne ssAutomation: Drive Continuous Value Creation and TransformEnterprise Operation in the Era of Digitalization,” White Paper, 2018(2) Yokogawa Ele ct r ic Cor p., “ Yokogawa’s Sy n apt ic Bu si ne ssAutomation Converging Intelligent Sensing with Plant ArtificialIntelligence (AI) to Drive Performance Optimization and SustainableValue Creation,” White Paper, 201968(3) Masahisa Saitou, Masato Yamaji, et al., “Sushi Sensor for AchievingIndustrial IoT Solutions,” Yokogawa Technical Report EnglishEdition, Vol. 61, No. 1, 2018, pp. 7-10* Sush i Sensor is a registered t radema rk of Yokogawa Elect r icCorporation.* LoRa is a registered trademark and LoRaWAN is a trademark ofSemtech Corporation.* All other company, organization, or product names, and logos thatappear in this paper are either trademarks or registered trademarks oftheir respective holders.* For details of the release overseas, please visit Yokogawa’s website.Yokogawa Technical Report English Edition Vol.62 No.2 (2019)14
Yokogawa released the first Sushi Sensor, a wireless vibration sensor, in March 2018. In July 2019, Yokogawa released wireless temperature and pressure sensors, expanding the sensor portfolio (Note 1: The wireless vibration sensor has been released in Japan and some other countries. Although the wireless pressure and temperature sensors are .
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