Middle East and Africa Predictive Maintenance Market – Industry Trends and Forecast to 2029

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Middle East and Africa Predictive Maintenance Market – Industry Trends and Forecast to 2029

  • ICT
  • Upcoming Reports
  • May 2022
  • MEA
  • 350 Seiten
  • Anzahl der Tabellen: 220
  • Anzahl der Abbildungen: 60

Middle East and Africa Predictive Maintenance Market, By Components (Solution, Services), Deployment Mode (Cloud, On-Premise), Organisation Size (Large Enterprises, Small and Medium-Sized Enterprises), Vertical (Manufacturing, Energy and Utilities, Transportation, Government, Healthcare, Aerospace and Defense, Others) - Industry Trends and Forecast to 2029

Middle East and Africa Predictive Maintenance Market

Market Analysis and Size

Predictive maintenance is known to lead a huge a huge increase in ROI. It can decline maintenance costs up to 25%-30%, decreases breakdowns to 70%-75% and reduces downtime to 35%-45%. These services are being highly deployed as they save overall cost for enterprises.

Middle East and Africa Predictive Maintenance Market was valued at USD 497.15 million in 2021 and is expected to reach USD 25878.63 million by 2029, registering a CAGR of 37.70% during the forecast period of 2022-2029. Manufacturing account for the largest vertical segment in the respective market owing to the rise in automation in the manufacturing sector. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team also includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.

Market Definition

Predictive maintenance refers to a technique that utilizes data analysis techniques and tools for detecting anomalies in business operations. These also detect possible defects in equipment and processes so that they can be fixed before they result in failure.

Report Scope and Market Segmentation

Report Metric

Details

Forecast Period

2022 to 2029

Base Year

2021

Historic Years

2020 (Customizable to 2014 - 2019)

Quantitative Units

Revenue in USD Million, Volumes in Units, Pricing in USD

Segments Covered

Components (Solution, Services), Deployment Mode (Cloud, On-Premise), Organisation Size (Large Enterprises, Small and Medium-Sized Enterprises), Vertical (Manufacturing, Energy and Utilities, Transportation, Government, Healthcare, Aerospace and Defense, Others)

Countries Covered

Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA).

Market Players Covered

IBM (US), SAP SE (Germany), Microsoft (US), Siemens (Germany), GENERAL ELECTRIC (US), Schneider Electric (France), Software AG (Germany), C3.ai, Inc. (US), DINGO Software Pty. Ltd. (Australia), Splunk Inc. (US), Oracle (US), Amazon Web Services, Inc. (US), Hitachi, Ltd. (Japan), ABB (Sweden), Huawei Technologies Co., Ltd. (China), Intel Corporation (US), and SKF (Sweden), among others

Market Opportunities

  • Need for real-time condition monitoring to assist in taking prompt actions
  • Increase in the usage of connected and integrated technologies
  • Rise in the emergence of big data analytics

Middle East and Africa Predictive Maintenance Market Dynamics

This section deals with understanding the market drivers, advantages, opportunities, restraints and challenges. All of this is discussed in detail as below:

Drivers

  • Need to Obtain New Insights

The increase in need to aggregate and explore textual data to obtain new insights acts as one of the major factors driving the predictive maintenance market. The incorporation of industry technology, knowledge, and practices to drive business outcomes has a positive impact on the market.

  • Emergence of Big Data Analytics

The rise in the emergence of big data analytics across the region accelerate the market growth. Numerous enterprises are focusing on combining disparate internal data along with external data sources for acquiring new efficiencies assist in the expansion of the market.

  • Prevent Unplanned Reactive Maintenance

The increase in the adoption of predictive maintenance programs to prevent unplanned reactive maintenance further influence the market. These services allows the maintenance frequency to be as low as possible for preventing unplanned reactive maintenance without incurring costs.

Additionally, rapid urbanization, change in lifestyle, surge in investments and increased consumer spending positively impact the predictive maintenance market.

Opportunities

Furthermore, need for real-time condition monitoring to assist in taking prompt actions and rise in internet proliferation extend profitable opportunities to the market players in the forecast period of 2022 to 2029. The increase in the usage of connected and integrated technologies will further expand the market.

Restraints/Challenges

On the other hand, factors such as data security concerns along with requirement of frequent maintenance and up gradation to keep the systems updated are expected to obstruct market growth. Also, lack of skilled workforce and complications with ownership and privacy of collected data are projected to challenge the predictive maintenance market in the forecast period of 2022-2029.

This predictive maintenance market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on predictive maintenance market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

COVID-19 Impact on Middle East and Africa Predictive Maintenance Market

The COVID-19 pandemic had a positive impact on the predictive maintenance market. It helped millions of people globally in leveraging advanced tools for various applications. The surge in the in investments by various SMEs and large enterprises in technologies such as like AI and machine learning for improving business operations. These services were highly useful during the pandemic due to the high need for remote monitoring and management of assets and business processes. The predictive maintenance is expected to witness high growth Post-COVID-19 due to the adoption of smart manufacturing processes using AI, and IoT technologies.

Middle East and Africa Predictive Maintenance Market Scope and Market Size

The predictive maintenance market is segmented on the basis of components, deployment mode, organisation size and vertical. The growth amongst these segments will help you analyze meager growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Components

  • Solution
  • Services

Deployment Mode

  • Cloud
  • On-Premise

Organisation Size

  • Large Enterprises
  • Small and Medium-Sized Enterprises

Vertical

  • Manufacturing
  • Energy and Utilities
  • Transportation
  • Government
  • Healthcare
  • Aerospace and Defense
  • Others

Middle East and Africa Predictive Maintenance Market Regional Analysis/Insights

The predictive maintenance market is analysed and market size insights and trends are provided by country, components, deployment mode, organisation size and vertical as referred above.

The countries covered in the predictive maintenance market report are Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA).

South Africa accounted largest market share is due to increasing concern towards improvement of uptime of equipment and maintenance cost reduction.

The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.   

Competitive Landscape and Middle East and Africa Predictive Maintenance Market

The predictive maintenance market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to predictive maintenance market.

Some of the major players operating in predictive maintenance market are

  • IBM (US)
  • SAP SE (Germany)
  • Microsoft (US)
  • Siemens (Germany)
  • GENERAL ELECTRIC (US)
  • Schneider Electric (France)
  • Software AG (Germany)
  • C3.ai, Inc. (US)
  • DINGO Software Pty. Ltd. (Australia)
  • Splunk Inc. (US)
  • Oracle (US)
  • Amazon Web Services, Inc. (US)
  • Hitachi, Ltd. (Japan)
  • ABB (Sweden)
  • Huawei Technologies Co., Ltd. (China)
  • Intel Corporation (US)
  • SKF (Sweden)


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Inhaltsverzeichnis

1 INTRODUCTION

1.1 OBJECTIVES OF THE STUDY

1.2 MARKET DEFINITION

1.3 OVERVIEW OF MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET

1.4 LIMITATIONS

1.5 MARKETS COVERED

2 MARKET SEGMENTATION

2.1 MARKETS COVERED

2.2 GEOGRAPHICAL SCOPE

2.3 YEARS CONSIDERED FOR THE STUDY

2.4 CURRENCY AND PRICING

2.5 DBMR TRIPOD DATA VALIDATION MODEL

2.6 MULTIVARIATE MODELLING

2.7 COMPONENTS LIFELINE CURVE

2.8 PRIMARY INTERVIEWS WITH KEY OPINION LEADERS

2.9 DBMR MARKET POSITION GRID

2.1 VENDOR SHARE ANALYSIS

2.11 SECONDARY SOURCES

2.12 ASSUMPTIONS

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

5 COVID-19IMPACT ON PREDICTIVE MAINTENANCE MARKET

5.1 AFTERMATH OF COVID-19 AND GOVERNMENT INITIATIVE TO BOOST THE MARKET

5.2 STRATEGIC DECISIONS FOR MANUFACTURERS AFTER COVID-19 TO GAIN COMPETITIVE MARKET SHARE

5.3 IMPACT ON DEMAND

5.4 IMPACT ON SUPPLY CHAIN

5.5 CONCLUSION

6 MARKET OVERVIEW

6.1 DRIVERS

6.1.1 INCREASING CONCERN TOWARDS IMPROVEMENT OF UPTIME OF EQUIPMENT AND MAINTENANCE COST REDUCTION

6.1.2 RISING DEMAND OF PREDICTIVE MAINTENANCE IN VARIOUS VERTICALS

6.1.3 INCREASING USE OF EMERGING TECHNOLOGIES TO GAIN VALUABLE INSIGHTS

6.1.4 RISING DEMAND OF SENSORS AMONG INDUSTRIES

6.2 RESTRAINTS

6.2.1 LACK OF SKILLED WORKERS

6.2.2 LOW LEVEL OF AWARENESS AMONG ENTERPRISES

6.2.3 TRUST ISSUES WITH PREDICTIVE MAINTENANCE TECHNOLOGY

6.3 OPPORTUNITIES

6.3.1 REAL-TIME MONITORING CONDITION TO ASSIST IN TAKING PROMPT ACTIONS

6.3.2 COVID-19 PANDEMIC RAISING THE NEED FOR REMOTE CONTROL AND MANAGEMENT OF PROPERTIES AND BUSINESS PROCESSES

6.3.3 RISING TECHNOLOGICAL INNOVATION

6.4 CHALLENGES

6.4.1 CONCERN OVER DATA SECURITY AND PRIVACY ISSUES

6.4.2 DEVELOPING FUNCTIONAL PREDICTIVE MAINTENANCE SOLUTIONS APPLICABLE TO MANUFACTURING

6.4.3 CONTINOUS UPGRADATION AND MAINTENANCE REQUIRED FOR SYSTEM

6.4.4 HIGH COST INVOLVED IN SETTING UP THE MACHINERY AND EQUIPMENT

7 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY COMPONENT

7.1 OVERVIEW

7.2 SOLUTIONS

7.2.1 INTEGRATED

7.2.2 STAND-ALONE

7.3 SERVICES

7.3.1 TRAINING & CONSULTING

7.3.2 IMPLEMENTATION

7.3.3 SUPPORT & MAINTENANCE

8 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE

8.1 OVERVIEW

8.1.1 ON-PREMISE

8.1.2 CLOUD

9 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY ORGANISATION SIZE

9.1 OVERVIEW

9.1.1 LARGE ORGANISATION

9.1.2 SMALL & MEDIUM ORGANISATION

10 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY VERTICALS

10.1 OVERVIEW

10.1.1 MANUFACTURING

10.1.2 ENERGY & UTILITIES

10.1.3 GOVERNMENT

10.1.4 HEALTHCARE

10.1.5 TRANSPORT

10.1.6 AEROSPACE & DEFENSE

10.1.7 OTHERS

11 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY GEOGRAPHY

11.1 MIDDLE EAST AND AFRICA

11.1.1 SOUTH AFRICA

11.1.2 SAUDI ARABIA

11.1.3 U.A.E

11.1.4 ISRAEL

11.1.5 EGYPT

11.1.6 REST OF MIDDLE EAST AND AFRICA

12 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: COMPANY LANDSCAPE

12.1 COMPANY SHARE ANALYSIS: MIDDLE EAST AND AFRICA

13 SWOT ANALYSIS

14 COMPANY PROFILE

14.1 IBM CORPORATION

14.1.1 COMPANY SNAPSHOT

14.1.2 REVENUE ANALYSIS

14.1.3 COMPANY SHARE ANALYSIS

14.1.4 PRODUCT PORTFOLIO

14.1.5 RECENT DEVELOPMENTS

14.2 SAP SE

14.2.1 COMPANY SNAPSHOT

14.2.2 REVENUE ANALYSIS

14.2.3 COMPANY SHARE ANALYSIS

14.2.4 PRODUCT PORTFOLIO

14.2.5 RECENT DEVELOPMENTS

14.3 SIEMENS

14.3.1 COMPANY SNAPSHOT

14.3.2 REVENUE ANALYSIS

14.3.3 COMPANY SHARE ANALYSIS

14.3.4 PRODUCT PORTFOLIO

14.3.5 RECENT DEVELOPMENTS

14.4 MICROSOFT

14.4.1 COMPANY SNAPSHOT

14.4.2 REVENUE ANALYSIS

14.4.3 COMPANY SHARE ANALYSIS

14.4.4 PRODUCT PORTFOLIO

14.4.5 RECENT DEVELOPMENT

14.5 GENERAL ELECTRIC

14.5.1 COMPANY SNAPSHOT

14.5.2 REVENUE ANALYSIS

14.5.3 COMPANY SHARE ANALYSIS

14.5.4 PRODUCT PORTFOLIO

14.5.5 RECENT DEVELOPMENTS

14.6 ABB

14.6.1 COMPANY SNAPSHOT

14.6.2 REVENUE ANALYSIS

14.6.3 PRODUCT PORTFOLIO

14.6.4 RECENT DEVELOPMENTS

14.7 AMAZON WEB SERVICES, INC. (A SUBSIDIARY OF AMAZON)

14.7.1 COMPANY SNAPSHOT

14.7.2 REVENUE ANALYSIS

14.7.3 PRODUCT PORTFOLIO

14.7.4 RECENT DEVELOPMENTS

14.8 C3.AI, INC.

14.8.1 COMPANY SNAPSHOT

14.8.2 PRODUCT PORTFOLIO

14.8.3 RECENT DEVELOPMENTS

14.9 DINGO SOFTWARE PTY. LTD

14.9.1 COMPANY SNAPSHOT

14.9.2 PRODUCT PORTFOLIO

14.9.3 RECENT DEVELOPMENT

14.1 HITACHI, LTD.

14.10.1 COMPANY SNAPSHOT

14.10.2 REVENUE ANALYSIS

14.10.3 PRODUCT PORTFOLIO

14.10.4 RECENT DEVELOPMENT

14.11 HUAWEI TECHNOLOGIES CO., LTD.

14.11.1 COMPANY SNAPSHOT

14.11.2 REVENUE ANALYSIS

14.11.3 PRODUCT PORTFOLIO

14.11.4 RECENT DEVELOPMENT

14.12 INTEL CORPORATION

14.12.1 COMPANY SNAPSHOT

14.12.2 REVENUE ANALYSIS

14.12.3 PRODUCT PORTFOLIO

14.12.4 RECENT DEVELOPMENT

14.13 ORACLE

14.13.1 COMPANY SNAPSHOT

14.13.2 REVENUE ANALYSIS

14.13.3 PRODUCT PORTFOLIO

14.13.4 RECENT DEVELOPMENT

14.14 PTC

14.14.1 COMPANY SNAPSHOT

14.14.2 REVENUE ANALYSIS

14.14.3 PRODUCT PORTFOLIO

14.14.4 RECENT DEVELOPMENTS

14.15 SCHNEIDER ELECTRIC

14.15.1 COMPANY SNAPSHOT

14.15.2 REVENUE ANALYSIS

14.15.3 PRODUCT PORTFOLIO

14.15.4 RECENT DEVELOPMENTS

14.16 SKF

14.16.1 COMPANY SNAPSHOT

14.16.2 REVENUE ANALYSIS

14.16.3 PRODUCT PORTFOLIO

14.16.4 RECENT DEVELOPMENTS

14.17 SOFTWARE AG

14.17.1 COMPANY SNAPSHOT

14.17.2 REVENUE ANALYSIS

14.17.3 PRODUCT PORTFOLIO

14.17.4 RECENT DEVELOPMENTS

14.18 SOFTWEB SOLUTIONS INC. (AN AVNET COMPANY)

14.18.1 COMPANY SNAPSHOT

14.18.2 REVENUE ANALYSIS

14.18.3 PRODUCT PORTFOLIO

14.18.4 RECENT DEVELOPMENTS

14.19 SPLUNK INC.

14.19.1 COMPANY SNAPSHOT

14.19.2 REVENUE ANALYSIS

14.19.3 PRODUCT PORTFOLIO

14.19.4 RECENT DEVELOPMENTS

14.2 UPTAKE TECHNOLOGIES INC

14.20.1 COMPANY SNAPSHOT

14.20.2 PRODUCT PORTFOLIO

14.20.3 RECENT DEVELOPMENTS

15 QUESTIONNAIRE

16 RELATED REPORTS

Tabellenverzeichnis

LIST OF TABLES

TABLE 1 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2018-2027 (USD MILLION)

TABLE 2 MIDDLE EAST AND AFRICA SOLUTION IN PREDICTIVE MAINTENANCEMARKET, BY REGION,2018-2027 (USD MILLION)

TABLE 3 MIDDLE EAST AND AFRICA SERVICES IN PREDICTIVE MAINTENANCE MARKET, BY REGION,2018-2027, (USD MILLION)

TABLE 4 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE, 2018-2027 (USD MILLION)

TABLE 5 MIDDLE EAST AND AFRICA ON-PREMISE IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 6 MIDDLE EAST AND AFRICA CLOUD IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 7 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY ORGANISATION SIZE, 2018-2027 (USD MILLION)

TABLE 8 MIDDLE EAST AND AFRICA LARGE ORGANISATION IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 9 MIDDLE EAST AND AFRICA SMALL & MEDIUMORGANISATION IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 10 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY VERTICAL, 2018-2027 (USD MILLION)

TABLE 11 MIDDLE EAST AND AFRICA MANUFACTURING IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 12 MIDDLE EAST AND AFRICA ENERGY & UTILITIES IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 13 MIDDLE EAST AND AFRICA GOVERNMENT IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 14 MIDDLE EAST AND AFRICA HEALTHCARE IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 15 MIDDLE EAST AND AFRICA TRANSPORT IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 16 MIDDLE EAST AND AFRICA AEROSPACE &DEFENSE IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 17 MIDDLE EAST AND AFRICA OTHERS IN PREDICTIVE MAINTENANCE MARKET, BY REGION, 2018-2027, (USD MILLION)

TABLE 18 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET , BY COUNTRY, 2018-2027 (USD MILLION)

TABLE 19 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2018-2027 (USD MILLION)

TABLE 20 MIDDLE EAST AND AFRICA SOLUTIONS IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 21 MIDDLE EAST AND AFRICA SERVICES IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 22 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE , 2018-2027 (USD MILLION)

TABLE 23 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY ORGANIZATION SIZE , 2018-2027 (USD MILLION)

TABLE 24 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY VERTICAL , 2018-2027 (USD MILLION)

TABLE 25 SOUTH AFRICA PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2018-2027 (USD MILLION)

TABLE 26 SOUTH AFRICA SOLUTIONS IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 27 SOUTH AFRICA SERVICES IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 28 SOUTH AFRICA PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE , 2018-2027 (USD MILLION)

TABLE 29 SOUTH AFRICA PREDICTIVE MAINTENANCE MARKET, BY ORGANIZATION SIZE , 2018-2027 (USD MILLION)

TABLE 30 SOUTH AFRICA PREDICTIVE MAINTENANCE MARKET, BY VERTICAL , 2018-2027 (USD MILLION)

TABLE 31 SAUDI ARABIA PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2018-2027 (USD MILLION)

TABLE 32 SAUDI ARABIA SOLUTIONS IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 33 SAUDI ARABIA SERVICES IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 34 SAUDI ARABIA PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE , 2018-2027 (USD MILLION)

TABLE 35 SAUDI ARABIA PREDICTIVE MAINTENANCE MARKET, BY ORGANIZATION SIZE , 2018-2027 (USD MILLION)

TABLE 36 SAUDI ARABIA PREDICTIVE MAINTENANCE MARKET, BY VERTICAL , 2018-2027 (USD MILLION)

TABLE 37 U.A.E PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2018-2027 (USD MILLION)

TABLE 38 U.A.E SOLUTIONS IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 39 U.A.E SERVICES IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 40 U.A.E PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE , 2018-2027 (USD MILLION)

TABLE 41 U.A.E PREDICTIVE MAINTENANCE MARKET, BY ORGANIZATION SIZE , 2018-2027 (USD MILLION)

TABLE 42 U.A.E PREDICTIVE MAINTENANCE MARKET, BY VERTICAL , 2018-2027 (USD MILLION)

TABLE 43 ISRAEL PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2018-2027 (USD MILLION)

TABLE 44 ISRAEL SOLUTIONS IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 45 ISRAEL SERVICES IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 46 ISRAEL PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE , 2018-2027 (USD MILLION)

TABLE 47 ISRAEL PREDICTIVE MAINTENANCE MARKET, BY ORGANIZATION SIZE , 2018-2027 (USD MILLION)

TABLE 48 ISRAEL PREDICTIVE MAINTENANCE MARKET, BY VERTICAL , 2018-2027 (USD MILLION)

TABLE 49 EGYPT PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2018-2027 (USD MILLION)

TABLE 50 EGYPT SOLUTIONS IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 51 EGYPT SERVICES IN PREDICTIVE MAINTENANCE MARKET, BY TYPE, 2018-2027 (USD MILLION)

TABLE 52 EGYPT PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE , 2018-2027 (USD MILLION)

TABLE 53 EGYPT PREDICTIVE MAINTENANCE MARKET, BY ORGANIZATION SIZE , 2018-2027 (USD MILLION)

TABLE 54 EGYPT PREDICTIVE MAINTENANCE MARKET, BY VERTICAL , 2018-2027 (USD MILLION)

TABLE 55 REST OF MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2018-2027 (USD MILLION)

 

Abbildungsverzeichnis

LIST OF FIGURES

FIGURE 1 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: SEGMENTATION

FIGURE 2 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: DATA TRIANGULATION

FIGURE 3 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: DROC ANALYSIS

FIGURE 4 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: MIDDLE EAST AND AFRICA VS REGIONAL MARKET ANALYSIS

FIGURE 5 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: COMPANY RESEARCH ANALYSIS

FIGURE 6 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: INTERVIEW DEMOGRAPHICS

FIGURE 7 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: DBMR MARKET POSITION GRID

FIGURE 8 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: VENDOR SHARE ANALYSIS

FIGURE 9 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: SEGMENTATION

FIGURE 10 RISING DEMAND OF PREDICTIVE MAINTENANCE IN VARIOUS VERTICALS IS EXPECTED TO DRIVE THE MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET IN THE FORECAST PERIOD OF 2020 TO 2027

FIGURE 11 SOLUTION SEGMENT IS EXPECTED TO ACCOUNT FOR THE LARGEST SHARE OF THE MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET IN 2020 & 2027

FIGURE 12 DRIVERS, RESTRAINTS, OPPORTUNITIES AND CHALLENGES OF MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET

FIGURE 13 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: BY COMPONENT, 2019

FIGURE 14 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: BY DEPLOYMENT MODE, 2019

FIGURE 15 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: BY ORGANISATION SIZE, 2019

FIGURE 16 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: BY VERTICAL, 2019

FIGURE 17 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET : SNAPSHOT (2019)

FIGURE 18 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET : BY COUNTRY (2019)

FIGURE 19 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET : BY COUNTRY (2020 & 2027)

FIGURE 20 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET : BY COUNTRY (2019 & 2027)

FIGURE 21 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET : BY COMPONENT(2020-2027)

FIGURE 22 MIDDLE EAST AND AFRICA PREDICTIVE MAINTENANCE MARKET: COMPANY SHARE 2019 (%)

 

Detaillierte Informationen anzeigen Right Arrow

Forschungsmethodik

Die Datenerfassung und Basisjahresanalyse werden mithilfe von Datenerfassungsmodulen mit großen Stichprobengrößen durchgeführt. Die Phase umfasst das Erhalten von Marktinformationen oder verwandten Daten aus verschiedenen Quellen und Strategien. Sie umfasst die Prüfung und Planung aller aus der Vergangenheit im Voraus erfassten Daten. Sie umfasst auch die Prüfung von Informationsinkonsistenzen, die in verschiedenen Informationsquellen auftreten. Die Marktdaten werden mithilfe von marktstatistischen und kohärenten Modellen analysiert und geschätzt. Darüber hinaus sind Marktanteilsanalyse und Schlüsseltrendanalyse die wichtigsten Erfolgsfaktoren im Marktbericht. Um mehr zu erfahren, fordern Sie bitte einen Analystenanruf an oder geben Sie Ihre Anfrage ein.

Die wichtigste Forschungsmethodik, die vom DBMR-Forschungsteam verwendet wird, ist die Datentriangulation, die Data Mining, die Analyse der Auswirkungen von Datenvariablen auf den Markt und die primäre (Branchenexperten-)Validierung umfasst. Zu den Datenmodellen gehören ein Lieferantenpositionierungsraster, eine Marktzeitlinienanalyse, ein Marktüberblick und -leitfaden, ein Firmenpositionierungsraster, eine Patentanalyse, eine Preisanalyse, eine Firmenmarktanteilsanalyse, Messstandards, eine globale versus eine regionale und Lieferantenanteilsanalyse. Um mehr über die Forschungsmethodik zu erfahren, senden Sie eine Anfrage an unsere Branchenexperten.

Anpassung möglich

Data Bridge Market Research ist ein führendes Unternehmen in der fortgeschrittenen formativen Forschung. Wir sind stolz darauf, unseren bestehenden und neuen Kunden Daten und Analysen zu bieten, die zu ihren Zielen passen. Der Bericht kann angepasst werden, um Preistrendanalysen von Zielmarken, Marktverständnis für zusätzliche Länder (fordern Sie die Länderliste an), Daten zu klinischen Studienergebnissen, Literaturübersicht, Analysen des Marktes für aufgearbeitete Produkte und Produktbasis einzuschließen. Marktanalysen von Zielkonkurrenten können von technologiebasierten Analysen bis hin zu Marktportfoliostrategien analysiert werden. Wir können so viele Wettbewerber hinzufügen, wie Sie Daten in dem von Ihnen gewünschten Format und Datenstil benötigen. Unser Analystenteam kann Ihnen auch Daten in groben Excel-Rohdateien und Pivot-Tabellen (Fact Book) bereitstellen oder Sie bei der Erstellung von Präsentationen aus den im Bericht verfügbaren Datensätzen unterstützen.

Häufig gestellte Fragen

Middle East and Africa Predictive Maintenance Market will be worth USD 25878.63 million By 2029.
Middle East and Africa Predictive Maintenance Market growth rate is 37.70% during the forecast period.
The Need to Obtain New Insights, Emergence of Big Data Analytics and Prevent Unplanned Reactive Maintenance are the growth drivers of the Middle East and Africa Predictive Maintenance Market.
Components, deployment mode, organisation size, and vertical are the factors on which the Middle East and Africa Predictive Maintenance Market research is based.
IBM (US), SAP SE (Germany), Microsoft (US), Siemens (Germany), GENERAL ELECTRIC (US), Schneider Electric (France), Software AG (Germany), C3.ai, Inc. (US), DINGO Software Pty. Ltd. (Australia), Splunk Inc. (US), Oracle (US), Amazon Web Services, Inc. (US), Hitachi, Ltd. (Japan), ABB (Sweden), Huawei Technologies Co., Ltd. (China), Intel Corporation (US), and SKF (Sweden), among others are the major companies in the Middle East and Africa Predictive Maintenance Market.