wipro.com Are You Doing Enough to Plug Revenue Leaks in Your Manufacturing Process?

wipro.com Are You Doing Enough to Plug Revenue Leaks in Your Manufacturing Process?

wipro.com Atiny Adidas factory in Ansbach, Germany, is currently drawing the attention of the manufacturing world. The factory will produce about 1 million running shoes for Adidas in the next few years!. Called a speed factory, the highly-automated plant is primarily designed for two things: to bring production back home to Germany and to give Adidas the capacity to respond faster to market changes with new types of shoes. A tertiary aim of the speed factory is even more exciting to make shoes on demand, using robots to turn out customized orders within a day. If costs can be kept under check, this customization represents both growth and margin expansion opportunities not possible with traditional manufacturing lines. So, it comes as no surprise that forward-thinking companies like Adidas and BMW are striving to deliver extreme customization using intelligent digitized production processes, connected IT and OT systems and Artificial Intelligence (AI) - all of them being key constituents of Industry 4.0. For most organizations, replicating this level of customization-and all the other cool things-made possible by Industry 4.0 tools and practices will take several years of perseverance. Should they wait 5 years to put up a super plant and harvest the benefits of Industry 4.0? We think there is a faster way to feel and use the power of Industry 4.0. We propose raising the Manufacturing Intelligence Quotient (MiQ) of manufacturing organizations using Industry 4.0 practices. MiQ is a philosophy a way of collating operating parameters with the sole purpose of drawing insights, and giving instant access and control of critical operating parameters to plant management. These parameters include exceptions, variance and impending failures and are triggered with events, a fundamental construct of Industry 4.0 and super factories. Under the MiQ umbrella we have a variety of applications such as Revenue Leak Analyzer and Smart Non-Conformance Management. The Revenue Leak Analyzer has special significance for manufacturing. Manufacturing veterans know that revenue leaks even in well-run Lean and Six Sigma operations. It does so for many reasons, starting from variances in plant to plant processes, mismatched labor and non-optimized planning. What makes this challenge daunting is the fact that collecting these parameters takes significant time, doggedness and cost. The Revenue Leak Analyzer differentiates itself from other performance analyzer tools and methods with its ability of decentralized edge analytics for real-time dynamic performance measure at production unit level for product operation activities. Hierarchical computation enables unit-level performance metrics to be aggregated at station and plant level for financial cost, productivity and quality, to provide business information in realtime. This provides an opportunity for informed decision-making and to align manufacturing strategy and accounting systems. The truth is that transactional process loss doesn't receive as much attention as it should. This is with good reason: it represents the lowest level of detail for profitability management and, in the past, has been difficult to accurately track the steady trickle and fix it in time.! Source: http://www.adidas- group.com/en/media/news-archive/press - releases/2016/adidasexpands-production-capabilities-speed factory-germany/ 2

Does your plant have Manufacturing Intelligence Quotient (MiQ)? It may help to explain this through an industry example. Imagine a manufacturer of sophisticated centrifugal compressors for the auto and home markets. The manufacturer has a target margin of 36% over the life of assembly of a compressor. However, due to production gaps and process complexities, there is a significant erosion of margins, which go down as low as 25% at the SKU level. The manufacturer is unable to tell in real time where the problems are. For a large organization, where the cost of quality could run into anything from $100 to $250 million, moving the needle by even 3% to 4% can be significant. The good news is that improving MiQ to plug revenue leaks is relatively simpler than launching the complete line up of Industry 4.0 technologies. This second level of detailed data has a second advantage it can also be used to provide root cause data to understand the where and the why of poor Overall Equipment Effectiveness (OEE) data that is somewhat akin to understanding why the patient s temperature has increased! Companies are waking up to the fact that the gaps reducing the value of their data must be bridged. What is becoming apparent is the need for granular, non-siloed and real-time information pertaining to product margins. These organizations are now ready to embark on the next level of maturity with MiQ and access significant gains. In our earlier example of the compressor manufacturer, first pass yield that typically hovers between 79% and 83% could improve to 93% after the introduction of a suitable MiQ application. The gain is significant, and is certainly noteworthy when you consider the fact that no changes are required to be made to the bill of material (BOM), plant equipment or operations manpower. Injecting MiQ into your plant Manufacturing plants need applications such as the Revenue Leak Analyzer that capture data with the right granularity, at the right leak points (see Figure 1), in real time. It has become much easier today to create and deploy these applications using modern interfaces, cloud technologies and real-time analytics. 3

Machine TPM/ Overall Equipment Effectiveness Manpower Energy Scheduled stops System disorders Setup time losses Change over time Short stop and load losses Procedural and organizational losses Rate losses Loss of quality machine System failure due to faults Setup and adjustment No load and short stops Decreased velocity Quality losses Reduced output and start-up losses Vacation, sick leave, absenteeism Overtime Planning losses Flow losses (waiting time) Quality losses Movements Unused energy consumption during production Unused energy consumption with reduced production Process Quality Material Losses due to idle and small stops Capacity losses Start up losses Operating Losses Quality losses Losses due to molds, tooling and fixtures Loss of volume Inventory losses First pass yield Scrap / rejects Rework Customer returns Assembly yield Loss of quality material Over production Inventory FG/RM Inventory turnover Figure 1: Possible Revenue Leak Points in Manufacturing These applications address the problems of aggregated, dated and siloed financial information pertaining to margin, inventory and profit. They solve the problem of margin leaks with near real-time insights through process mining techniques applied on a per unit cost basis and relate it to process gaps. In other words, a Revenue Leak Analyzer captures the event that causes the leak at an SKU level, assigns a cost to the event and shows this in real time. The trick is to make sure the expertise to implement the solution at the right points in the manufacturing process is available. It is here that organizations must consider a technology partner that makes data the center for all strategic and tactical change. What happens after an organization or a plant has such MiQ applications in place? Once the applications are deployed, the insights they deliver can be further improved. The clues to improved performance lie in enriching the analytical data by supplementing it with data from other systems such as PLM and SCADA. However, as must be clearly apparent, that is a topic which rightfully deserves a deeper discussion in the future. 4

About The Author Sudhi Bangalore is General Manager and Head of Smart Manufacturing at Wipro. With over 14 years of experience in industrial engineering and business operations across industry segments, Sudhi s responsibilities include strategy, market growth and P&L management for Smart Manufacturing. He was involved in the creation of Plant Technology Solutions group and the go-to-market partnership with a major European company. Prior to this, he headed Wipro s Industrial Automation division. Sudhi holds a Masters in Industrial Engineering from University of Louisville and an MBA from Kent University. He can be reached at sudhi.bangalore@wipro.com. About Wipro Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading information technology, consulting and business process services company that delivers solutions to enable its clients do business better. Wipro delivers winning business outcomes through its deep industry experience and a 360 degree view of Business through Technology. By combining digital strategy, customer centric design, advanced analytics and product engineering approach, Wipro helps its clients create successful and adaptive businesses. A company recognized globally for its comprehensive portfolio of services, strong commitment to sustainability and good corporate citizenship, Wipro has a dedicated workforce of over 170,000, serving clients across 6 continents. For more information, please visit wipro.com or write to us at info@wipro.com 5

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