. Tsunami Warning System (TWS) consist detection and notification system that mostly operated by countries affected by Tsunami . For Malaysi a, it is not cost effective to use cutting edge TWS. The reason is it free from big earthquakes where its location far from tectonic plate boundaries . Besides , it’s surrounded by neighbouring countries which act lik e natural wall to prevent natural disaster reach to Malaysia territory . Fatal Tsunami happened on 2004 has chan ged this fact and Malaysia is expose d to secondary effect of natural disaster happened at neighbouring countries. An earthquake with magnitude nine (9) occurred at Banda Aceh was generate Tsunami wave that propagate from Indonesia to Malaysia coastline killed 68 people . As an immediate action , Malaysian government introduce Malaysia Tsunami Early Warning System (SAATNM) which the technology behind the system is from imported equipment. Unfortunately, this sophisticated equipment is costly to maintain and it’s expose d to vandalise. Thus, ADIBs is acronyms for Aware Tsunami Detection Interconnected Built -In System is a TWS propose by authors to help Malaysian government agencies to develop a low cost and reliable TWS suitable for Malaysia usage. The authors also propose a novel method to calculat e Tsunami risk which considers severity of Tsunami , occurrence of Tsunami and detection of Tsunami. Tsunami Failure Mode Effect Analysis (TFMEA) has successful informs Malaysia should focus on prevention works rather than using expensive TWS. Keywords: ADIBs , Tsunami Warning System , Tsunami Failure Mode Effect Analysis 1. Introduction 1.1 Malaysia Tsunami History On 26 -December -2004, an undersea earthquake with magnitude 9.0 happened near Sumatra , Indonesia killed over 200,000 people at six (6) countries (Indonesia, Sri Lanka, India, Thailand, Somalia and Malaysia). The remembrance tragedy was followed by deadliest tsunami struck the states located northern of Malaysia which sacrificed 68 people [1]. Malaysia is a Southeast Asia country w here its location is geo -strategic that’s safe from earthquakes, tsunami, volcanoes eruption and tornados. After the tragedy, there is no guarantee the safe conditi on will lasting forever. Malaysia are exposed to secondary effect of natural disaster happened at neighboring countries. Figure 1 to Figure 6 shows the destruction at affected location after hit by Tsunami. Within short time, the victims losses their houses, valuable belongings and more sad were losing their family members in front of their eyes. Malaysian is mooted with long time history without any big natural disaster occurred except bad flooding . They were surprised and not expect that Tsunami waves can reach to their coastline. Inside F igure 7 shows an indicator that Malaysia is a “protected country” which free from active volcanoes and far away from tectonic pl ates boundaries as in Figure 8 . It’s also located at center of Southeast Asia that’s surrounded by neighboring countrie s like Indonesia, Philippine and Cambodia. Their function is like “ natural walls” that reduce or eliminate outside threats from reach to Malaysia. Despite of this believe, the Sunda Arc is major active plate boundary where Indo-Australia Plate is subducted at 70mm/year under the Eurasian plate caused earthquakes and potential to generate Tsunami [11]. Thus, t he Tsunami happened on 2004 was triggered the Malaysian government to get ready for future threats and they must to make sure the sad tragedy will not repeated. As a result, Malaysia National Tsunami Early Warning System (SAATNM) was established on 2005 by Malaysian Meteorological Department (MET Malaysia) [12]. Figure 1 Tsunami at Acheh, Indonesia [2 ] Figure 2 Tsunami at Ampara, Sri Lanka [3] Figure 3 Tsunami at Madras , India [4] Figure 4 Tsunami at Phuket, Thailand [5] Figure 5 Tsunami at Puntland ,Somalia [6] Figure 6 Tsunami at Kuala Muda , Malaysia [7 ] Figure 7 Active V olcanoes in South east Asia (Malaysia Inside Purple C ircle is free from volcanoes) [8] Figure 8 Tectonic Plates in Southeast Asia . Malaysia Inside Red Circles (Above) and Subduction at Sunda Trench caused Earthquake (Below) [9] [10] 1.2 Malaysia Tsunami Risk Analysis Based Figure 9 and Figure 10, there have potential Tsunami can occur at West and East of Malaysia according to historical data of earthquakes. Risk assessment of Tsunami can be calculated by using Tsunami Failu re Mode Effect Analysis (TFMEA) method. This method is first ever in the world proposed by authors to determine Severity of Tsunami (ST), Occurrence of Tsunami (OT) and Detection of Tsunami (DT). The severity of Tsunami (ST) is determined according to research conducted by International Research Institute of Disaster Science (IRIDeS), Tohoku University. The data of 100 world historical tsunami was selected based on earthquake larger than 7.5 magnitude and the seismic events after years 1600 AD [15]. Then, the data is filtered by authors according to 2 criteria and tabulated in Table 1. The first criterion is the tsunami was occurred in Southeast Asia and the second criterion is it’s happened at neighbouring countries near to Malaysia coastline . The authors classified the Severity Rank based on how big the Severity of Effect to numbers of Deaths, Damage and House Destroyed. The numbers of Deaths is the first factor followed by value of Damage in million dollar and numbers of house destroyed. The numbers or values are benchmark ed to historical Tsunami data in Table 1. Table 2 shows the Severity of Tsunami (ST) proposed by authors with Severity Rank from one (1) to ten (10). Severity Rank is added in side Table 1 at last column to determine the severity of Tsunami happened at South East Asia. As summary, Malay sia is exposed with severe Tsunami happen at neighbouring country especially West Malaysia which near to Sunda Trench was recorded highest Tsunami severity rank compared to East Malaysia has lower Tsunami severity rank. This claim is same as a conclusion made by a research conducted by geologist at University of Malaya [16]. Table 1 Summary of Tsunami Filtered by A uthors No. Year Location Maximum Water Height (m) Deaths (ppl) Damage ($Mill.) House Destroyed Severity Rank 1 1897 Sulu Sea 7.0 13 No data 33 7 2 1975 Philippine Trench 3.0 0 No data 30 5 3 1977 Solomon Island 0.04 0 0 0 1 4 1996 Sulawesi 7.7 9 1 400 7 5 2004 Sumatra 50.9 227,899 10,000 No data 10 Table 2 Severity of Tsunami (ST) Effect Severity of Effect Severity Rank SMALL EARTHQUAKE No tsunami 1 BIG EARTHQUAKE No tsunami 2 SMALL TSUNAMI No destruction. Maximum water height less than 1 meter 3 BIG TSUNAMI No destruction. Maximum water height more than 1 meter 4 DAMAGE Low number of damage (<1$Mill.) or house destroyed (<100) or both 5 FATAL Low number of deaths (<100ppl) but no damage and house destroyed 6 FATAL & DAMAGE Low number of deaths (<100ppl) and damage (<1$Mill.) or house destroyed (<100) or both 7 SMALL DESTRUCTION Massive number of damage (>1$Mill.) or house destroyed (>100) or both 8 BIG DESTRUCTION Massive number of deaths (>100ppl), but no damage and house destroyed 9 TOTAL DESTRUCTION Massive number of deaths (>100pp l) and damage (>1$Mill.) or house destroyed (>100) or both 10 Figure 9 Potential Tsunamigenic Zoned based on Historical Earthquakes Near to West Malaysia [13] Figure 10 Potential Tsunamigenic Zoned based on Historical Earthquakes Near to East Malaysia [14] Occurrence of Tsunami (OT) is frequency of earthquakes occur at one place that are able to generate Tsunami. It’s shows as an indicator of region al instability. Data recorded in Figure 12 shows that earthquakes with high magnitude are seldom to happen compared to earthquakes with low magnitude are frequently happen. In Figure 11, only Zone A, B, C, D, E and H are selected as subject of study because these zones are near to Malaysia Coastline. From earthquakes return period data, the authors propose OT as in Table 3. Higher Occurrence Rank of Tsunami has higher probability for Tsunami to generate. Figure 11 Map of South East Asia with Divided by Zone as Source of Earthquakes [17] Figure 12 Estimate d Return Period of Earthquakes at South East Asia [17] Table 3 Occurrence of Tsunami (OT) Probability of Occurrence Tsunami Occurrence Reason Probability P eriod Occurrence Rank VERY LOW Very low earthquake magnitude 3 to 3.5 Every couple of days 1 LOW Low earthquake magnitude 3.5 to 4 Every week or couple of weeks 2 Low earthquake magnitude 4 to 4.5 Every couple of weeks or every month 3 MODERATE Moderate earthquake magnitude 4.5 to 5 Every month or couple of months 4 Moderate earthquake magnitude 5 to 5.5 Every couple of months or every year 5 Moderate earthquake magnitude 5.5 to 6.5 Every year or couple of years 6 HIGH High earthquake magnitude 6.5 to 7 Every couple of years 7 High earthquake magnitude 7.5 to 8 Every 10 to 30 years 8 High earthquake magnitude 8 to 8.5 Every 30 to 50 years 9 VERY HIGH Very high earthquake magnitude 8.5 to 9 Every 50 years or more 10 Lastly , Detection of Tsunami (DT) is measure ment degree of tsunami detection . The possibility of detections are divided into five (5); VERY FAST DETECTION, FAST DETECTION, SLOW DETECTION and TOO SLOW DETECTION. Table 5 shows the Detection of Tsunami (DT) according to Tsunami Bulletin Issue (TBI) . Tsunami Bulletin Issue is period taken after seismic event to inform public to start mitigation or precaution. This is based on data of Tsunami Warning System (TWS) developed by several coun tries as tabulated in Table 4 below. Some countries are taking longer time to release TBI because they allocate extra time to conduct details analysis . Thus, they can avoid false TBI . For example is India TWS required 30 minutes to release TBI . Based on past earthquakes database, the epicentre centre was happened far away from their country . Thus, the tsunami wave was taking more t han 30 minutes to reach to their coastline. Table 4 Tsunami Warning System (TWS) for Asia Countries Tsunami Warning System (TWS) Tsunami Bulletin Issue (TBI) Japan After 3 minutes [18] Iran After 4 minutes [19] Indonesia After 4.5 minutes [11] Oman After 5 Minutes [19] Malaysia After 12 minutes [20] India After 30 minutes [13] Table 5 Detection of Tsunami (DT) Possibility of Detection Tsunami Warning System (TWS) Readiness Tsunami Bulletin Issue (TBI) Detection Rank VERY FAST DETECTION VERY FAST After 1 minute of earthquake 1 VERY FAST After 2 minute s of earthquake 2 FAST DETECTION FAST After 3 minute s of earthquake 3 FAST After 4 minute s of earthquake 4 FAST After 5 minute s of earthquake 5 SLOW DETECTION OK After 6 to 7 minute s of earthquake 6 OK After 8 to 9 minute s of earthquake 7 OK After 9 to 10 minute s of earthquake 8 OK After 10 to 11 minute s of earthquake 9 TOO SLOW DETECTION NOT OK After 12 minute of earthquake 10 Tsunami Risk Priority Number (TRPN) is a total number of multiplications ST, OT and DT. The TRPN number can be used to prioritise the list of risk . The highest number of TRPN will be put as first priority of risk to be evaluate d and propose a counter -measure. When a counter measure is taken, the TRPN number must reduce compare to initial TRPN without any countermeasure. Fatality is more severe compared to loss es of others thing . Therefore, the authors make a conclusion that a risk with ST equal or more than six (6) MUST assign a counter -measure. Figure 13 shows all 13 states in Malaysia are evaluated by using TRPN . An analyse is conducted to evaluate how serious the risk of Tsunami to their coastline. In Table 6, the Priority of Tsunami Risk is divided into three ( 3); HIGH RISK, MEDIUM RISK and LOW RISK based on TRPN. Perlis, Kedah, Pulau Pinang, Perak and Selangor are li st of state (No.1 to 5) that expose d to MEDIUM RISK of Tsunami. Their ST is six (6) because in 2004 they had experienced fatal Tsunami. While other states, not havin g any single Tsunami happened. Thus, their ST is one (1). For OT, the same states and also Sabah have highest number which is eight (8). The reason is their locations are near to neighbouring countries like Indonesia and Philippines that frequently expose d to high magnitude of earthquakes. The rest of states have OT equal to one (1). However, all states have same DT. Refer to Table 7 for details. As summary, Tsunami Failure Mode Effect Analysis (TFMEA) proposes by authors is a novel method to help rela ted government agencies to evaluate Tsunami risk at their country. For Malaysia, result of analysis shows five (5) from 13 states is in MEDIUM RISK and the rest is in LOW RISK. Counter measures must be taken either by prevention or detection to reduce the risk from MEDIUM RISK to LOW RISK. Then, safety of public can be ensured. This analysis must conduct before implementation of Tsunami Warning System (TWS). Therefore, by this risk assessment can identify which locations need government to put as high prior ity. Figure 13 TRPN Evaluation based on States in Malaysia Table 6 Priority of risk based on TRPN Tsunami Risk Priority Number (TRPN) Priority of Tsunami Risk 729-1000 HIGH RISK 210 - 728 MEDIUM RISK 1 - 209 LOW RISK Table 7 TFMEA for Malaysia without TWS State Tsunami Failure Mode Effect Analysis (TFMEA) Priority of Tsunami Risk Severity of Tsunami (ST) Occurrence of Tsunami (OT) Detection of Tsunami (DT) Tsunami Risk Priority Number (TRPN) 1-Perlis 6 8 10 480 MEDIUM RISK 2-Kedah 6 8 10 480 MEDIUM RISK 3-Pulau Pinang 6 8 10 480 MEDIUM RISK 4-Perak 6 8 10 480 MEDIUM RISK 5-Selangor 6 8 10 480 MEDIUM RISK 6-Negeri Sembilan 1 1 10 10 VERY LOW RISK 7-Melaka 1 1 10 10 VERY LOW RISK 8-Johor 1 1 10 10 VERY LOW RISK 9-Pahang 1 1 10 10 VERY LOW RISK 10-Kelantan 1 1 10 10 VERY LOW RISK 11-Terengganu 1 1 10 10 VERY LOW RISK 12-Sarawak 1 1 10 10 VERY LOW RISK 13-Sabah 1 8 10 80 VERY LOW RISK 2. Methodology ADIB s is acronym for Aware Tsunami Detection Interconnected Built-In System . It’s a low -cost Tsunami Warning System (TWS) that currently develop by authors . ADIBs consist existing sub- system and it using more than 80% local made components as stated inside Table 8 . The technology of components inside sub -system is commercially available and made by local original equipment manufacturer (OEM) . Figure 14 below shows ADIBs conceptual image. Figure 14 ADIBs Conceptual Table 8 ADIBs Sub -system ADIBs Sub-system Classification of Sub-system New or Existing Local or Import or Mix Tide Gauge (Power devices, Controller devices , Measurement devices , Transmitter devices , Protection devices ) New Local Anchor New Local Vertical Flexi -Cable Structure New Local Telecommunication Tower Existing Mix Siren New Local SCADA (Software , Hardware) New Local Data storage New Local Summary 86% New 14% Existing 86% Local 14% Mix The distance of tide gauge at sea is below than 35km from coastline where it’s depend on maximum distance signal can transmit from tide gauge to telecommunication tower. Roughly check through Google Map in Figure 15 shows that distance between Banda Aceh t o Langkawi is circa 471km. On 2004, Tsunami hit Malaysia at Pantai Cenang, Langkawi on 12:45pm after tsunami wave travel 3 hours from Banda Aceh [21]. Based on this fact, the Tsunami wave moving speed is circa 157km/hour. Worse comes to worst, the tsunami warning must announce within 3 hours from earthquake occur. It’s also depending on location of epicenter. More near the epicenter to Malaysia territory, less time required to release Tsunami Warning. Figure 15 Distance between Banda Acheh to Langkawi (Google Map) Therefore, ADIBs offering cost effective solution for Malaysia n government to replace buoys system that already obsolete caused by vandalism and not functioning [22] . The expensive cost to replace with new one and for conduct regular maintenance is the main factor why Malaysian government stop from using buoys type TWS and only fully depend on tide gauges and tsunami information from neighbouring countries. Estimation cost for replace a new buoy is about RM 3 million and maintenance co st is about RM 0.5 million [23]. Unfortunately, these tides gauges are normally installed near to coastline not at open s ea. Consequently, late detection of tsunami wave usually happen because they only able to observe sudden change of tide wave reading when tsunami wave is very near to coastline . In Figure 16 shows the tide gauges were installed at port and light house. Figure 16 Malaysia Tide Gauges near to coastline [20] Moreover, data recorded from Tsunami on 2004 in Figure 17 proven that tide gauge at Langkawi only can detect anomaly reading on 12:00PM which is 45 minutes before Tsu nami hit Pantai Cenang on 12:45PM. From this finding , there is potential high fatality caused by time -lapse for Tsunami warning reach to people and insufficient evacuation time because of traffic conjunction and crowded people. Thus , highly suggest installing ADIBs as frontline Tsunami d etection that help to increase detection time and give more time for evacuation process . Figure 17 Tidal records from Langkawi indicating sea levels during the tsunami (Dept. of Survey & Mapping Malaysia) [21] According t o risk analysis result in Table 7 , Malaysia ’ states at northern region are exposing to MEDIUM RISK of Tsunami. Then, in Figure 18 , 19 and 20 are suggesting locations to install ADIBs. By install ADIBs, priority risk of TRPN can be lowered and increase detection time. Figure 18 ADIBs at Langkawi, Kedah Figure 19 ADIBs at Kuala Kedah, Kedah ADIBs ADIBs Figure 20 ADIBs at Batu Feringgi, Pulau Pinang Figure 21 ADIBs at Pulau Pangkor, Perak Figure 22 ADIBs at Sekinchan, Selangor 3. Results & Discussions Malaysia TWS with ADIBs can help to reduce ST from six ( 6) to five ( 5) as highlighted by green colour inside Table 9 . That means, only fatal can be eliminated with early Tsunami detection system. Destruction caused by Tsunami can’t be avoided if there still have buildings or any human made structures near to coastline. Even though the TWS is equipping with advance and expensiv e Tsunami detection system, it’s only improve the detection time but not prevent the destruction. Thus, Malaysian government should focus on prevention works such as coastal protection and rehabilitation and shoreline management. While for TWS is highly ad visable to use low -cost system that is cheaper to be replace if damage or vandalise and easy to maintain. ADIBs also can help to improve current tsunami detection time. TWS with coastal tide gauges only can detect tsunami early 45 minutes meanwhile TWS with ADIBs where it’s located maximum 35km from coastline can detect early 1 to 3 hours (Still under investigation for exact time). Table 9 TFMEA for Malaysia with ADIBs State Tsunami Failure Mode Effect Analysis (TFMEA) Priority of Tsunami Risk Severity of Tsunami (ST) Occurrence of Tsunami (OT) Detection of Tsunami (DT) Tsunami Risk Priority Number (TRPN) 1-Perlis 5 8 10 400 MEDIUM RISK 2-Kedah 5 8 10 400 MEDIUM RISK 3-Pulau Pinang 5 8 10 400 MEDIUM RISK ADIBs ADIBs ADIBs 4-Perak 5 8 10 400 MEDIUM RISK 5-Selangor 5 8 10 400 MEDIUM RISK 6-Negeri Sembilan 1 1 10 10 VERY LOW RISK 7-Melaka 1 1 10 10 VERY LOW RISK 8-Johor 1 1 10 10 VERY LOW RISK 9-Pahang 1 1 10 10 VERY LOW RISK 10-Kelantan 1 1 10 10 VERY LOW RISK 11-Terengganu 1 1 10 10 VERY LOW RISK 12-Sarawak 1 1 10 10 VERY LOW RISK 13-Sabah 1 8 10 80 VERY LOW RISK 4. Conclusion As summary, Techno Brozek Enterprise is Malaysian company that currently develop a local Tsunami Warning System (TWS) called ADIBs. This low cost TWS is using available technology which more than 80% of sub -system components made by local OEM. They also introduce Tsunami Failure Mode Effect Analysis (TFMEA) as a novel approach to calculate Tsunami risk. TFMEA result informs that Malaysia should implement low cost TWS like ADIBs and focus on prevention works to eliminate destruction caused by Ts unami. Acknowledgments The present work was fully funded by Tech no Brozek Enterpise to help Malaysian government agencies to develop a local low -cost and reliable Tsunami Warning System (TWS). Any further inquires, can contact at technobrozek@gmail .com .