multi-criteria assessment for the optimization of lean ... j. and guo, j.: survey of worldwide pico-...

Multi-criteria Assessment for the Optimization

of Lean Satellite Programs

Pauline FAURE, Atomu TANAKA, Mengu CHO, HORYU-IV Team

Kyushu Institute of Technology

Laboratory of Spacecraft Environment Interaction Engineering

1st IAA Latin American Symposium on Small Satellites

-Advanced Technologies and Distributed Systems –

March 7th – 10th 2017

Ministry of Science, Technology and Productive Innovation, Palermo, Buenos Aires, Argentina

Session on Small Satellites Worldwide: Achievements and Trends

CONTENTS

1. Introduction

2. Research objectives

3. Methodology

4. Results and discussion

5. Summary

6. Research outlook

1st IAA Latin American

Symposium on Small Satellites

March 7th - 10th 2017

Buenos Aires, Argentina 2

CONTENTS

1. Introduction

3. Methodology

5. Summary

6. Research outlook

INTRODUCTION

Lean satellite programs essence

Non-traditional and risk-taking development approach

Development drivers: fast delivery, low cost, value

EgyptSat1, SaudiSat3

Credit: NARSS

Thai-Paht (Thailand)

Credit: SSTL

BADR1 (Pakistan)

Credit: SUPARCO

New comers, universities

Dove2 (U.S.)

Credit: Planet Labs Inc.

SDS series (Japan)

Credit: JAXA

CHEOPS (CH, ESA)

Credit: ESA

Private sector, space agencies

Low cost

Fast delivery

INTRODUCTION

Lean satellite programs essence

Non-traditional and risk-taking development approach

Development drivers: fast delivery, low cost, value

Buenos Aires, Argentina

LEAN SATELLITE

Satellite that utilizes non-traditional, risk-taking development and management

approaches with the aim to provide value of some kind to the customer at low

cost and without taking much time to realize the satellite mission

IAA Study Group 4.18 Members, IAA Study on Definition and Requirements of Small Satellites Seeking Low-Cost and Fast-Delivery, Version 13, June 2016

INTRODUCTION

Problems

Non-traditional satellites present the highest rate of infant mortality

Database

1394 satellites (all categories included) launched between Jan. 1990 and Oct. 2008

~97.4% ~98.6% ~98.2%

Dubos, G.F., Castet, J-F. and Saleh, J.H.: Statistical Reliability Analysis of Satellites by Mass Category: Does Spacecraft Size Matter?, Acta Astronautica 67, 2010, pp. 584-595

*Reliability = probability of non failure

INTRODUCTION

Problems

Database

178 CubeSats launched until June 30, 2014

Langer, M. and Bouwmeester: Reliability of CubeSats – Statistical data, developers’ beliefs and the way forward, Proc. of the 30th Annual AIAA/USU Conf. on Small Satellites

*Reliability = probability of non failure

INTRODUCTION

Bouwmeester, J. and Guo, J.: Survey of worldwide pico- and nanosatellite missions, distributions and subsystem technology, Acta Astronautica 67, 2010, pp. 854-862

Database

94 satellites (pico- and nano-satellite categories) launched until July 30, 2009

Problems

Most of non-traditional satellites fail to achieve full mission success

INTRODUCTION

Problems

Most of non-traditional satellites fail to achieve full mission success

Testing prior to launch is insufficient

No value provided to the customer

How to improve lean satellite programs?

INTRODUCTION

Plan for improvement: PI2 action plan

Prevent infant mortality

Identify culprit sub-systems

Improve testing strategy

CONTENTS

1. Introduction

3. Methodology

5. Summary

6. Research outlook

RESEARCH OBJECTIVES

Study the relation between testing time vs. reliability vs. project schedule vs. cost

Demonstrate lean satellites reliability, i.e. value, improves through testing

Serve as guidance to lean satellite programs developers

CONTENTS

1. Introduction

3. Methodology

5. Summary

6. Research outlook

METHODOLOGY

First and foremost, some vocabulary

Failure: any mistake, malfunction, anomaly, or glitch in the hardware or software (misplaced hole, power line inversion, component short-circuit, etc…)

Engineering model 1 (EM1): assembly and test of the bus sub-systems only (no payload)

Engineering model 2 (EM2): assembly and test of the bus and payload sub-systems + fit check between structural elements and electronic boards

Flight model (FM): same as EM2 + no major design or hardware modifications allowed

Reliability: probability of non-failure at a certain given time

Testing: include assembly, integration, and testing processes

METHODOLOGY

Experimental data collection methodology

Failures number, discovery time, and type of failures recorded

General time assumption: testing from Monday through Friday, 8h/day

Data collection

period

METHODOLOGY

Simulation algorithm steps

1) Random number

generation

Decision on whether a

failure occurred or not

2) Failure modes

determination

Estimation of failure

influence on testing time

3) Failure criticality level

determination

Estimation of failure

reparation on project schedule

r(t): failure rate

4) Reliability after launch

calculation based on 1000 runs

CONTENTS

1. Introduction

3. Methodology

5. Summary

6. Research outlook

RESULTS and DISCUSSION

Failure discovery over time

Most of failures discovered during the early stage of new testing phase

Testing to be performed for as long as 1 year

Experimental data Simulations (example)

Faure, P., Tanaka, A. and Cho, M.: Toward lean satellites reliability improvement using HORYU-IV project as case study, Acta Astronautica (2017), DOI:

10.1016/j.actaastro.2016.12.030

Failure discovery over time

Most of failures discovered during the early stage of new testing phase

Testing to be performed for as long as 1 year

Experimental data Simulations (example)

50h of testing

Discovered failures > 50%

150h of testing

Discovered failures > 2/3

10.1016/j.actaastro.2016.12.030

Failures taxonomy

Engineering model 1 (EM1)

Only bus sub-systems assembled and tested

No payload sub-systems tested

10.1016/j.actaastro.2016.12.030

Failures taxonomy

Engineering model 2 (EM2)

Bus and payload sub-systems assembled and tested

First time assembly of structural and electronic parts

10.1016/j.actaastro.2016.12.030

Failures taxonomy

Flight model (FM)

Similar to EM2

No major design or hardware changes allowed

Testing time vs. reliability vs. project schedule

Increase of interfaces number increases system complexity and drives

down its reliability

Optimum testing time to prevent infant mortality

Faure, P., Tanaka, A., Cho, M. and HORYU-IV Team: Study for the Optimization of Lean Satellite Programs Managerial Decision-making, Selected paper of the 67th

International Astronautical Congress (2016), to be submitted to Acta Astronautica for publication

Experimental data

Optimum testing time to ensure lean concepts of cost, time, and value

Simulations (1000 runs)

Qualitative results

(1 month)

・Ti: ×10

・Total testing time at Ti=200h: 2061h

(~12 months of testing)

・Total project time at Ti=200h: 5563h

(~32 months)

・Number of failures: ×1.7

・Reliability: ×11

Qualitative results

(1 month)

Qualitative results

・Ti: ×2.5

・Total testing time at Ti =50h: 540h

(~3 months of testing)

・Total project time at Ti=50h: 3165h

(~18 months)

・Number of failures: ×1.3

・Reliability: ×6

Cost vs. project schedule

Hardware, software, and personnel costs taken into account

Importance of smart automation of testing

From Ti=20h to Ti=200h,

cost: +70%

CONTENTS

1. Introduction

3. Methodology

5. Summary

6. Research outlook

SUMMARY

Most of failures appear during the early stages of testing

Failures mostly driven by bus sub-systems and interfaces

Proper testing prior to launch can help preventing infant mortality

A too drastic testing time can drive drastic schedule and cost overruns

A mild testing time can greatly improve reliability after launch without impeding

program schedule or cost constraints

Overall, research results point out that there is an optimum testing time to

guaranty value to customer without impeding a considered program’s

schedule and cost requirements

CONTENTS

1. Introduction

3. Methodology

5. Summary

6. Research outlook

RESEARCH OUTLOOK

Research current limitations

Only one case study

Complexity of lean satellite not taken into account

Only qualitative trends established

Cannot determine optimal testing time for a considered lean satellite

Data from other lean satellite programs are needed

Not only university-based programs, but also private and

government-based programs

Not only from Japan, but all around the world

RESEARCH OUTLOOK

Countermeasures no.1

“Failures track sheet”

Template example

RESEARCH OUTLOOK

“Failures track sheet”

HORYU-IV “failures track

sheet” (FM excerpt)

RESEARCH OUTLOOK

“LeanSat community” lessons learned database

For example, take inspiration from NASA lessons learned system

NASA lessons learned system:

https://llis.nasa.gov/

RESEARCH OUTLOOK

Then, in the near future…

Based on collected data, development of an integrated

management tool (schedule, cost, reliability, others…)

Qualitative and quantitative trends projection

Specifics depending on different lean satellite approaches (university,

private, government)

“Base recipe” for successful lean satellite programs development

Etc…

Multi-criteria Assessment for the Optimization of Lean Satellite Programs

1st IAA Latin American Symposium on Small Satellites

-Advanced Technologies and Distributed Systems –

March 7th – 10th 2017

Ministry of Science, Technology and Productive Innovation, Palermo, Buenos Aires, Argentina

Pauline FAURE*, Atomu TANAKA, Mengu CHO*, HORYU-IV Team

*Corresponding authors contact:

faure.pauline-louise545@mail.kyutech.jp and cho@ele.kyutech.ac.jp

multi-criteria assessment for the optimization of lean ... j. and guo, j.: survey of worldwide pico-...

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