Design of Informatics-based Services in Manufacturing Industries: A Framework and Case Studies

Transcription

1 The 7 th CIRP IPSS Conference May 2015 Saint-Etienne, France Design of Informatics-based Services in Manufacturing Industries: A Framework and Case Studies by Chie-Hyeon Lim*, Min-Jun Kim, Jun-Yeon Heo, and Kwang-Jae Kim Department of Industrial and Management Engineering Pohang University of Science and Technology (POSTECH) *[email protected]

2 Informatics-based services in manufacturing industries Our focus Scope of PSS Product ICT Product related data Informatics Information Knowledge Use of the information in service Informatics -based service Heavy equipment Equipment health data Health diagnosis and prognosis information Prognostics and health management (PHM) service Agricultural machine Machine operations data Information on precise farming Precise farming service Vehicle Vehicle operations and health data Information on the vehicle and driving Vehicle operations and health management (VOHM) service 2

3 Research question Product Product related data How to design informatics-based services Informatics -based service Large ship Ship operations and voyage data Ship operations management service Wearable devices Human bio-signal data? Wearable device-based fitness service Product X Data Z Service Y 3

4 Design framework: Version 2.0 Informatics-based service design process Design support tools Data collection Data analysis Service opportunity identification Information content production Service concept design Service delivery process design

5 Overview of the case studies Informatics-based service design process <Case study 1> Vehicle operations and health management (VOHM) service <Case study 2> Driving safety enhancement service Data collection Data analysis Service opportunity identification Information content production Service concept design Service delivery process design Preparation of data from the vehicle relationship management (VRM) DB vehicle operations and health data Identification of VOHM Production of VOHM information content Integration of data from the digital tachograph (DTG), driver, and accident DBs vehicle operations and accident data Identification of Production of information content for driving safety management Design of Design of

6 Case study 1: With HYUNDAI (1/6) Preparation of data from the vehicle relationship management (VRM) DB Vehicle relationship management (VRM) database vehicle operations and health data Vehicle operations data Vehicle health data Identification of VOHM Production of VOHM information Data collection Data fields DB size Collects operations data in "trip" Trip start/end time, Average speed, Distance 7.6M trips (18,943 vehicles) Records every health data for 7 seconds when a warning code occurrs Warning code, Temperature, RPM 3,662 cases of warning codes 6

7 Engine oil deterioration measurement index 1 Case study 1: With HYUNDAI (2/6) Preparation of data from the vehicle relationship management (VRM) DB vehicle operations and health data Identification of VOHM Production of VOHM information Engine oil deterioration measurement index 2 Mean value of index 2 (4.2%) Mean value of index 1 (47.7%) 7

8 Case study 1: With HYUNDAI (3/6) Preparation of data from the vehicle relationship management (VRM) DB Data analysis perspectives Distribution of the data fields (e.g., velocity) Service opportunities Opportunity 1 vehicle operations and health data Identification of VOHM Production of VOHM information Driver sex Driver age Driving date/time Driving cost Driving safety Driving area Vehicle and consumable type Car stalling and warning code Driving capability enhancement (6) Context-aware driving support (7) Customer relationship management (8) Car and life (5) Opportunity 2 Opportunity 6 Opportunity 7 Opportunity 13 Opportunity 14 Opportunity 21 Opportunity 22 Opportunity 26 8

9 Case study 1: With HYUNDAI (4/6) Preparation of data from the vehicle relationship management (VRM) DB vehicle operations and health data Identification of VOHM 14분 9초 운행 Production of VOHM information 45분 4초 운행 1시간 33분 20초 운행 27분 33초 운행 20분 16초 운행 11분 17초 운행 9

10 Case study 1: With HYUNDAI (5/6) Preparation of data from the vehicle relationship management (VRM) DB vehicle operations and health data Identification of VOHM Production of VOHM information 10

11 Case study 1: With HYUNDAI (6/6) Preparation of data from the vehicle relationship management (VRM) DB vehicle operations and health data Identification of VOHM Production of VOHM information 11

12 Case study 2: With the Government (1/3) Integration of data from the digital tachograph (DTG), driver, and accident DBs DTG DB Accident DB Driver s Driving History DB DTG and accident data Identification of Data collection Collects operation data every second (Regularly uploaded) Collects accident data in the event of an accident Collects data at the time the driver joins the company Production of information for driving safety management Data fields Distance, GPS, Speed, Brake on/off, RPM Accident time, Location, Weather, Accident severity level Name, Age, ID card number, License number Design of Design of Current status Collected data of 3,342 vehicles Bus: 2,365 (483 GB) Truck: 931 (51 GB) Taxi: 46 (15 GB) Collected data of 6,329 drivers Bus: 4,289 Truck: 490 Taxi: 1,550 Collected data of 4,557 drivers Bus: 2,437 Truck: 886 Taxi: 1,234 12

13 Case study 2: With the Government (2/3) Integration of data from the digital tachograph (DTG), driver, and accident DBs DTG and accident data Identification of Production of information for driving safety management Design of 10 * p-value < 세로축: 시간당 평균 위반 횟수 5 1½Ã ç ±ÞÁÂÈ ÀüȽ¼ö - 가로축: 위험운전 행동 ½Ã ç ±Þ ì È ÀüȽ¼ö 0 1½Ã ç ±ÞÀ ÅÏȽ¼ö Design of Dangerous drivers 13

14 Driving safety index Case study 2: With the Government (3/3) Integration of data from the digital tachograph (DTG), driver, and accident DBs DTG and accident data Identification of Production of information for driving safety management Design of Time (sec.) Poor Fair Good Design of 14

15 Lessons learned: Challenges in designing informatics-based services Data collection 1. Collecting the right data for services Data analysis 2. Planning the data analyses for service design Service opportunity identification 3. Understanding the informatics-based services in question Information content production 4. Identifying the right information for customers Service concept design Information delivery service process design 5. Compromising different stakes on the concepts 6. Designing the appropriate delivery processes for customers 15

16 Future research Framework version 3.0 with more tools, a refined process, and more case studies Product ICT DB Informatics Information Knowledge Service design Informatics -based service concept Passenger vehicle VRM DB Driving patterns and vehicle health information VOHM Commercial vehicle DTG DB + Accident DB Driving patterns and accident Rates Driving safety enhancement service concept Human Body Personal wellness record DB Personal wellness indices Smart wellness Human Body National Health Insurance Service DB Likelihood of hypertension onset Hypertension management service concept 16

17 Concluding remarks Some keywords in the current information economy: Big Data Analytics, Internet of Things (IoT), Industry 4.0 This study Views phenomena in this economy from a service-oriented perspective Contributes to service design/innovation in manufacturing industries Proposing a framework for the design of informatics-based services in manufacturing industries Reporting on real case studies Providing lessons learned 17