*IDC (2021) Worldwide Asset Performance Management Software Forecast, 2021–2025: Market Growth Momentum Propelled by Ecosystem Expansion
With repair centers all over the world, traditional operations cannot respond to users' repair requests in a timely manner and manage repair operation information, including repair progress and spare parts management, which has become a challenge that brand owners need to solve.
Use wareconn platform to handle the repair progress of global service centers in real time, and implement spare parts inventory management. And the system's automatic warning helps to prepare parts in advance. The platform can be used to manage service centers and suppliers in various regions, and further analyze the repair records, so as to discover potential problems and room for improvement of product quality, performance, reliability and customer satisfaction.
Due to the system incompatibility, the test report of the service center for the repaired product needs to be manually recorded and sent by email. In addition to being time-consuming and inefficient, it is also prone to human error.
Through the wareconn platform, the repair center can record and compile the test data of the returned product in real time, and automatically connect it back to the brand's database through the API. Brand owner only needs to view the reports from their own systems, no additional import jobs are required. 100% automatic operation, saving manpower and improving process efficiency, and realizing systematic and instant operation tracking management of the entire warranty process.
The operation management systems of brand and suppliers are incompatible. When there is an RMA application, manual review is required, and the response time can be very long, and is impossible to respond to the demand immediately. The management of spare parts and the logistics of returned goods also require manual operation, which means it is difficult to track the repair history.
wareconn helps to sort out the whole process of after-sales service in the service center and can be connected with the customer's internal system. The customer only needs to submit the warranty application in the internal system, and send it back to wareconn through the API interface. The progress will be automatically created and approved. The administrator accounts can be assigned according to requirements, so that the RMA of 309 data centers around the world is not limited by time difference, and can be effectively managed 24/7. Global spare parts management will be carried out, and advanced exchange replacement can be taken place to shorten the service time. Statistical summary functions such as service report and defect records can help suppliers review and improve product quality.
Procurement and maintenance contract of asset management by using traditional Excel and paper work, without filing and classification, and it is difficult to check the warranty period or out-of-warranty. Inspection, maintenance, self-maintenance and supplier repairs are recorded separately, and there is no summary and serial unified tracking statistical KPIs. It is difficult to calculate the quantity, amount, repair and other costs of spare parts after the manufacturer's door-to-door service and replacement.
Using the wareconn and the Asset Management APP, the contract management function is connected in series from the installation, contract, daily maintenance, self-maintenance records, and supplier maintenance records. Actively drive repair and maintenance to achieve the purpose of early warning maintenance. And using statistical analysis for all records to generate visual graphs, get product reliability analysis, MTBF/MTTR, and trigger automatic reminders to reduce risks. Through the asset management solution, the production and operation efficiency can be improved, the manual work hours is reduced by 80%, and the inventory turnover cycle can be reduced by 40%.
Pain Points
M customer as the top one in data center field needs to process service through multiple systems
No integrated system for tracking a complete servicing process
Easy to lose FA report due to off-line discussion
No cloud-based solution for third-party service center connection
Total Solution
With API support, enable quick response to process and state communication
Flexiable service modes support
Pain Points
Difficult to manage and track historical service records
Scattered offline Excel records, resulting in consolidation inconvenience
No systematical collection on analysis report from OEM/ ODM
Easy to lose quality report from different customers
Total Solution
Handle batch RTV business by clicks
Available to eliminate unecessary return with failure analysis procedure'
Pain Points
No systematic management for the warranty contract between customers and suppliers
Unavailable to track the service status
Spend much time on expense settlement and chart creating
Inconvenient to real-time track the operation progress
Total Solution
Deploy relaible gloabal service network
Simplify servicing process by integration and purify warranty management by automation
Pain Points
No system records the warranty information of all asset and spare parts
Easy to lose paper file maintenance reports
Messy cost settlement operation and difficult to summarize the quality status
Unable to manage the entire warranty process in one system
Total Solution
Clear warranty information on every asset
Warranty claims, contract management, service record and bills are avaialbe to share on one-stop platform
Pain Points
No connection between manufacturers and service center to make preparations in advance
Chaotic process on the defective and spare parts delivery process
Separate and various service report to be mailed repeatedly or omitted
Manual summarize the maintenance costs and charts analysis
Total Solution
Enhance everything by change nothing
Combine world-wide service resources and cooperate with build-in systems
Pain Points
Unavialble to summarize various maintenance information in time, and find out the batch defectives immediately
Delayed communication on the physical maintenance data
Manual maintenance data is difficult to find historical record
Difficult to predict product return and prepare fixtures and manpower arrangements in advance
Total Solution
Fulfill data consolidation and transparency
Save communication time and find out the core value of warranty claims
In response to the ESG trend, enterprises are actively promoting energy-saving and carbon reduction management, especially in the environment of global supply chain restructuring. While considering energy-saving, are they also facing challenges in effectively managing assets? With the rise of Industry 4.0, the management mindset under the demographic dividend of the past few years may also need to accelerate digitization. In addition to implementing Manufacturing Execution System (MES), how should the corresponding asset management system be selected? Is it just to digitize asset management-related operations (inspection, maintenance, repair), or can it effectively improve asset reliability, reduce unexpected downtime, and even improve asset utilization value through data analysis of asset maintenance processes? Research indicates that asset maintenance costs can account for anywhere from 0.5% to 25% of enterprise revenue [1]. The choice of digitized system management will seriously affect the enterprise's operating performance and profitability.
Under the guidance of Industry 4.0 and intelligent technology, the era of emerging technology trends has arrived. Whether it is robot technology or artificial intelligence, automation, advanced materials and manufacturing, the Internet of Things, cloud co
Under the drive of the Industry 4.0 era, the basis of the corresponding transformation opportunities for after-sales service lies in data. Whether it's enterprises focusing on the development of connected products, the transformation of XaaS business model, digital transformation, installation excellent, resilient supply chains, omni-channel services, the deployment of digital twins as service enablers, or providing intelligent analytics, these all increase the importance of warranty data acquisition and analysis. Especially when facing the emergence of new technology products, geopolitical supply chain reorganization, and the shift of the customer experience economy, the overall industry strategy is gradually shifting from product-centric to customer-centric intelligent experiences[1].
Under the guidance of Industry 4.0 and intelligent technology, the era of emerging technology trends has arrived. Whether it is robot technology or artificial intelligence, automation, advanced materials and manufacturing, the Internet of Things, cloud co
In response to the ESG trend, enterprises are actively promoting energy-saving and carbon reduction management, especially in the environment of global supply chain restructuring. While considering energy-saving, are they also facing challenges in effectively managing assets? With the rise of Industry 4.0, the management mindset under the demographic dividend of the past few years may also need to accelerate digitization. In addition to implementing Manufacturing Execution System (MES), how should the corresponding asset management system be selected? Is it just to digitize asset management-related operations (inspection, maintenance, repair), or can it effectively improve asset reliability, reduce unexpected downtime, and even improve asset utilization value through data analysis of asset maintenance processes? Research indicates that asset maintenance costs can account for anywhere from 0.5% to 25% of enterprise revenue [1]. The choice of digitized system management will seriously affect the enterprise's operating performance and profitability.
Under the drive of the Industry 4.0 era, the basis of the corresponding transformation opportunities for after-sales service lies in data. Whether it's enterprises focusing on the development of connected products, the transformation of XaaS business model, digital transformation, installation excellent, resilient supply chains, omni-channel services, the deployment of digital twins as service enablers, or providing intelligent analytics, these all increase the importance of warranty data acquisition and analysis. Especially when facing the emergence of new technology products, geopolitical supply chain reorganization, and the shift of the customer experience economy, the overall industry strategy is gradually shifting from product-centric to customer-centric intelligent experiences[1].
On March 22, 2023, the European Commission officially adopted a new proposal Right to Repair (R2R), which is a common rule advocating for product repair by reducing waste to save consumers expenses, while supporting the goal of sustainable consumption under the European Green Deal [1].
On March 22, 2023, the European Commission officially adopted a new proposal Right to Repair (R2R), which is a common rule advocating for product repair by reducing waste to save consumers expenses, while supporting the goal of sustainable consumption under the European Green Deal [1].
Curious about how AI is revolutionizing manufacturing? From predictive maintenance to supply chain optimization, AI is transforming every facet of the sector. Our blog takes you through real-world examples of manufacturing businesses that leverage AI in their operations to enhance efficiency and maximize their impact globally.
As cyber threats become increasingly sophisticated, integrating artificial intelligence (AI) into cybersecurity is more than a passing trend — it’s a groundbreaking shift in protecting our digital assets. As cyber-attacks grow increasingly complex, leveraging AI becomes crucial for staying ahead of emerging threats.
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Ten years ago, data centers mainly focused on storing a large number of servers in predictable environments. The main priorities were capacity, reliability and redundancy, with little thought given to adaptability or efficiency. Moving forward to five years ago, users started demanding services that could scale based on their requirements - leading to a shift towards cloud computing. Today, Artificial Intelligence (AI) is pushing data centers to their limits due to the massive amount of generated data. JLL’s Data Centers 2024 Global Outlook report states that by 2027, AI advancement is projected to more than double the demand for global data center storage capacity.
These days our data are collected everywhere in the internet and are also used to train large language models like ChatGPT. But how do we train artificial intelligence (AI), how do we avoid distortions – known as bias – in the models and how do we ensure that data are protected? Reinhard Heckel, a professor of machine learning at the Technical University of Munich (TUM), takes the time to answer these questions. Prof. Heckel conducts research on large language models and medical imaging applications.
Predictive maintenance technologies and data management plans for maintenance managers to optimize equipment performance and integrate AI effectively.
Facilities Managers need to Commit to Preventative Maintenance.
Technology is pivotal in transforming equipment maintenance in today’s rapidly evolving industrial landscape. Traditional maintenance strategies, which relied heavily on reactive fixes and scheduled downtimes, are being replaced by advanced technological solutions to enhance efficiency, reduce costs, and minimize unexpected breakdowns.
The EU’s regulation on the Ecodesign for Sustainable Products (ESPR) comes into force today, but the required implementation of Digital Product Passports across sectors by 2030 entails a massive restructuring of data management across supply chains.
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