Rapid changing technologies (Artificial intelligence, Machine Learning, Robotics, Integration, Automation, Blockchain, Cloud Computing, etc.) pace of drift for traditional manufacturing enterprises in this new generation towards fourth industrial revolution (Industry 4.0). To not left behind with competitors and technologies this rapid change is important to implement among enterprises. For manufacturer now the technology-driven market is not that easy to handle. To address manufacturing industries here are the challenges-

Primary challenges:

• IOT; in order to perform digital transformation so many changes amend for every process, like IOT and Industry 4.0 link together to perform digitalization but security is a major concern to tackle with. More new technology-driven applications implemented more network security and encryption issues need to be solved quickly. Automation of so many technologies under one umbrella is also a question for Industry 4.0.
• Cybersecurity; in this networking era enterprises connected to smart networks, but security concerns are still on the bottleneck. Cybercrimes—phishing, hacking, malware attacks, etc. are more frequent and sophisticated. Cybersecurity is another big challenge for Industry 4.0.
• Big data; acquisition of automated data another big challenge for Industry 4.0. Data-complexity, -scalability, -legacy, -transformation are on automation stack for digital transformation. Big data is hard to process on a single run with correct executable information.
• ERP (enterprise resource planning); it is not a one-man army game, so many tasks to perform in ERP with so many manpower. Proper planning, communication, and technical job implementation are essential for any enterprise. The downfall in ERP solutions due to—infrastructure investment, high cost-rate, compatibility issues, proper analysis, lack of training, etc.
• Product-centric organization; It is better to drift business models to customer-focused perspective because it can add value to their customers by providing good profits at their end. Customer focused models increase more retention and acquisition for customers as compare to product-focused model.
• Industrial big data analytics; data management and data analytics are major challenges in this big data era. Distributed data sources bring (to bring these different source data together is a big task) hinderance in sharing, access, and integration of data.
• Framework design (proper road map for industries); enterprises are eager to enter in fast-paced technology-driven approach, but they are seeking for good road map with—asset maintenance, how it can add value for them, estimated ROI return, and cost-effective.

Secondary challenges:

• Comprehensive integration solution; enterprises not pre-integrated before services due to that fall, service-oriented architecture (SOA) principles cannot implement along.
• Market development; enterprises moving from product to service line to increase finances.
• Social impact; digitalization tremendously growing but user value is still not up to the mark for digitalization.
• Sustainable production (products without waste); as the market is competitive the way production is also cutting-edge with mass production, but mass customization is already in a pipeline. More data to handle for appropriate information.
• Geo-political and macro-economic context are very uncertain.
• Unclear digital supply chain strategy; supply chain leaders mentioned that digitization directly impacts the business but implementation to supply chain is still a question.
• Competitive landscape; due to fast pace technology upgrade many enterprises disruptive.
• To the point approach, is required to tap into innovations and revenue generation.

At Reliable Software we work with you to embrace your enterprise with correct fast-driven technologies at correct time with recent trend of data exchange and automation in manufacturing enterprises.