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How Industrial Companies Can Use Data to Attain Manufacturing Excellence

Posted by Julia Walsh on Nov 17, 2022 6:54:00 AM

Data has always been critical to process improvement and quality control in manufacturing. It is also the main driver of research and development. Manufacturers use data on the performance of their existing products to embed more features, update technology, and introduce new upgrades or novel products that perform better and thereby deliver greater value to their customers and their companies.

Since data has always been there and has always been used for improving operations, one wonders what’s so different about Industry 4.0, its emphasis on big data, and the potential benefits big data can bring to a manufacturing value chain. To answer this, we need to understand the nature of big data and the way its use can deliver unprecedented improvements and efficiency gains.

Understanding Big Data

Traditionally, vital manufacturing process data was recorded on manual forms. This data was later analyzed to reveal everything from equipment effectiveness to product-quality parameters. Over the years, manufacturers’ ability to capture process data improved with process automation and the ability to extract data directly through spreadsheets or PLC/SCADA applications. However, this data still needed to be formatted, streamlined, analyzed, and converted to insights.

Big data is different. It signifies data pertaining to each shop-floor transaction and beyond and covers everything from a part or assembly sitting on a warehouse shelf to WIP to finished goods being prepared for dispatch. Furthermore, it encompasses data beyond organizational boundaries like supply-chain partner and customer data.

 

Big data is generated at a high speed. Literally every transaction that happens on the floor creates data that is bulky in nature because a large amount of structured and unstructured data contributes to it. This data comes from a wide variety of sources inside and outside operations, even from social media. In the case of consumer products, the data varies in accuracy and requires specific tools for standardization and analysis. Analyzing big data could reveal unknown facts and trends that could help improve operations and spur innovation within manufacturing value chains.

However, harnessing and handling big data is challenging for most manufacturers. Though most understand the value of continuously generated data, they do not have the overarching system architecture to utilize the data generated within their value chains and beyond. Even in highly automated processes, for example, data from the shop floor might be collected for every single event, but unless it is put into context and enables decision-making it is not necessarily adding any value to operations.

BCG cites three main challenges faced by manufacturers in the process of attaining data excellence: lack of effective applications, technological challenges, and hurdles within the organization.

Most manufacturers lack the digital infrastructure and internal know-how needed to extrude actionable intel from the raw data pouring in. These are the technological challenges. Furthermore, they lack the application infrastructure that would enable the analysis and contextualization of data. Lastly, there is a lack of clear organizational strategy, no clear definition of roles and responsibilities, and insufficient skills and capabilities coupled with rigid internal processes and governance practices. All of this poses a challenge to attaining manufacturing excellence through big data to the extent that BCG states that only 17% of manufacturers have been able to capture the value of advanced analytics even though 72% clearly believe that analytics are of great importance in improving productivity.

While it is clear that big data has great potential for manufacturers, it is also evident that extracting value from it requires a proper application infrastructure, know-how, and a process blanket that does not allow valuable data to escape. Next, Webalo experts will share the ways manufacturers can achieve excellence through data analytics.  

Webalo Insights: Achieve Manufacturing Excellence by Getting Data Analytics Right

Webalo is a workforce-digitization and process-optimization platform that can act as the missing piece in a company’s application infrastructure and help them derive the maximum value out of their digital transformation efforts. As a solution, Webalo helps manufacturers connect the dots in data capture and management, and it does so by integrating enterprise applications with automation and MES-level applications. The platform also digitizes all workflows, and data capture and reporting are made convenient through the use of a mobile interface that allows workers to capture and use real-time process data. 

 

PWC describes six key ways that data analytics can help manufacturers achieve data-driven excellence. Let’s look at each one from a Webalo perspective.

Supply-Chain Optimization- Supply chains play a more important role than ever given the uncertainty in the global market caused by the pandemic and geopolitical situations. In times of turbulence, it is extremely important to have a close and well-coordinated relationship with supply-chain partners. Webalo helps achieve this by providing complete tracking and traceability for all material, WIP, and other inputs, allowing process owners to effectively manage inventory.  Due to its integration with enterprise and customer applications, Webalo can help guide better supply-chain planning and decision-making. Hyperconnectivity and integration allow for supply-chain optimization through Webalo.

Production Scheduling- Webalo allows workers and managers to develop and deploy their own mobile applications and modify them to better meet business and operational priorities. This can do wonders for effective production scheduling, as it becomes a real-time and dynamic activity. Events happening in the supply chain or the market can be quickly translated to changed production schedules. The whole thing comes back to big data and its effective use. For example, a changed order or spec in the ERP can immediately lead to stopped or rerouted production, with work instructions modified on the go by managers or engineers on their mobile devices. Not only does this make operations proactive, it also prevents any loss due to wrong production and prevents rework. 

Sales Forecasting- Webalo creates a complete Workforce Intelligence Center for manufacturers that uses data from production and the shop floor to drive business insight and decisions. Sales forecasting can be done in the Webalo apps through the analysis of live production data and product-consumption or sale trends. Webalo can also help maintain a leaner inventory and reduce just-in-case inventories. Information from the Workforce Intelligence Center goes far beyond operational improvement and can also help manufacturers better determine future demand trends.    

Reduced Costs- Webalo has a direct impact on costs because it allows faster and more accurate data-driven decision-making. In time-sensitive events like breakdowns and quality events where an OOS event occurs, the speed at which containment and CAPA actions get triggered can determine the amount of money lost. With Webalo, a fully mobile and composable platform, any event triggers immediate action based on its nature and intensity. The CAPA data further fuels the platform with information that helps personnel attain prescriptive analyses and prevent production and quality events before they happen simply by studying the trends and charts the application throws their way.    

Product Innovation- Manufacturing companies are often called out for not hearing the customer’s voice and not paying heed to what is truly needed. With platforms like Webalo, companies can view real-time market data and correlate it with their own production data to understand what product features are appreciated and what design aspects need improvement. It is imperative that gained intelligence is converted to action, and this is where Webalo and the integration it provides can prove critical.

Asset Management and Reliability- As the amount of automation within manufacturing processes increases and manufacturers rely increasingly on robots, equipment uptime and utilization become increasingly important. With Webalo, a mobile-maintenance workforce can ensure that asset utilization and machine uptime is always optimal.  A combination of AR technology and cross-functional collaboration enabled through the platform allows proactive maintenance to happen and ensures maintenance-related data and triggers are acted upon in real time.

Big-data analytics has many benefits, but the biggest is improved decision-making that is faster and more data driven. Webalo allows this to happen by not only capturing process data but also allowing integration-driven contextualization and decision-making within the platform functionality. It forms the process envelope needed to generate the true value of big data. So, if you are looking for the missing piece in your transformation efforts that can help digitize your workflows and capture manufacturing value, look at Webalo. It makes manufacturing excellence through data analytics a reality!