Challenges faced by Companies in Manufacturing Sector

The challenges faced by manufacturing industries vary across the various different lines of business, from raw materials to transporting finished goods to customers. Firstly Mainly, manufacturing companies are forced to park a lot of capital in purchase and maintenance of high level of inventories. Inflation rate growth has been constant over the years, leading to huge operational costs for manufacturers. The price of raw materials, trained labor, machinery etc., and almost everything has shot up.

In view of globalization & to remain competitive, the delivery response times are scheduled to be unrealistic, making it a tough job for everyone, from management to workers in the firm.Unrealistic timelines can affect the quality of production, which in-turn affects the morale of employees. Also, there is the problem of over-production and under-production as firms are not estimating the gap between demand and supply

How will analytics help solve these problems

To achieve a breakthrough in many of the core challenges in manufacturing industry, management should invest in advanced information technology along with enhancing the domain of R&D. With Big data and analytics in place, manufacturers can take faster, more perspicacious strategic decisions based on real-time information. Manufacturing analytics will help in reducing the amount of capital required for procuring, storing and maintain raw materials., Day-to-day activities like risk associated with employee safety, preventive maintenance of machinery etc. can be predicted using analytics. ERP tools are being used for data sharing between multiple process lines within the organization. This single source of data is used for performing a lot of industrial analytics. Machine learning techniques are used to automate quality checks. Predictive analytics helps in identifying supply and demand gap, which will help in the appropriate production of goods to match the demand.  Analytics on big data can reduce processing flaws, resulting in more realistic timelines. In short, any business problem can be addressed with big data analytics.

Why Innodatatics?

Professionals at Innodatatics will continuously strive to focus not only on the problems that the customers are facing, but also contributes significantly to RCA. We rely on our Robust analytical capabilities to derive actionable insights that help Manufacturers to take strategic decisions, to remain Competitive.

Our R&D team takes into consideration various aspects and expertise such as Customer analytics, sentiment analytics, Optimization techniques, product breakdown prediction models etc. into consideration, which augment innovations, thereby giving players in this sector a competitive edge in these dynamic market conditions.

Case Study 1:   How to manage the supply-chain based on products’ sales prediction View full Case study
Case Study 2 :   How to automate manual inspection of circuits on assembly chain process by image processing using Deep Learning
Case Study 2 :   How to automate manual inspection of circuits on assembly chain process by image processing using Deep Learning
Case Study 3 :   How to reduce blade manufacturing lot rejection by predicting the lot, which exceeds the lot rejection threshold
Case Study 4 :   Want to know how to reduce the warranty cost of heavy machinery sold to customers, by predicting the machinery failure & adjusting the warranty period
Case Study 4 :   Want to know how to reduce the warranty cost of heavy machinery sold to customers, by predicting the machinery failure & adjusting the warranty period