The Approach for shop floor and Enterprise monitoring

The manufacturing industry is not well equipped to respond to drastic changes in demand. Now, CxOs can use the powerful Enterprise Analytics Dashboard (EAD) analytics tool to forecast and manage demand - in real time.

The Approach for shop floor and Enterprise monitoring
Arunima Thakur
HCL Americas
Sidhartha Bala
HCL Technologies India

Introduction:

Manufacturing is one of the worst hit industries in the current economic downturn. Driven largely by the bullish mood of the market as well as that of consumers in the last four to five years it was in the expansion mode till the year 2008 also when the first signs of recession surfaced. The following couple of quarters saw the worst global meltdown where markets crashed, banks became insolvent, and credit dried up hurting the demand severely. Thus what at first appeared to be a financial meltdown was deep enough to stay, spread and affect the whole supply demand equation and hence the entire manufacturing industry.
The manufacturing industry by nature is not well equipped in responding to drastic changes in demand, the reason being most of the input costs are fixed and any effort to ramp up or ramp down production by large volumes is a costly step. . Therefore faced with demand crunch manufacturers are normally faced with either ramp down production by closing units or reduce prices to boost demand. Neither of them is a long term feasible solution as the industry already operates under tight margins and costs are fixed.
Cutting down manufacturing costs seems to be the obvious solution, but it’s easier said than done. However to stay competitive manufacturers are giving it a serious thought and examining it with a very keen eye in all dimensions.
Manufacturing processes are ingrained with inefficiencies. The reasons are manifold:
1. During a bull market the focus shifts to achieving incremental revenues as it's an easier way to make money
2. Manufacturing processes are run as silos with different owners trying to maximize their own goals rather than look at the overall picture
3. The overall picture is not so evident to the top management due to lack of visibility into the operations
Now interestingly the first two points talk about why it was not so important until now and the third is the roadblock preventing the elimination of the inefficiencies.
In an ideal factory, equipments would operate 100 percent of the time at 100 percent capacity, with an output of 100 percent good quality. In real life, however, this situation is rare. The difference between the ideal and the actual situation is due to the complex and interdependent processes which make it mathematically impossible to extract the entire 100% from the facility. Therefore calculating the overall equipment effectiveness (OEE) rate is a crucial element of any serious commitment to reduce equipment and process related wastes. OEE empowers manufacturing organizations to systematically improve processes and in turn, ensures improved consistency, quality, and productivity – all resulting in measurable and direct bottom line savings.
Possible ways of OEE Optimization:

Today, most of the manufacturing industries are using process automation equipment which has some information gathering capability related to its process. This capacity can range from a simple sensor counting number of outputs and also has the capability of raising alarms in case of any defects in the process. Capturing this information at a central location will help in initiating the troubleshooting process immediately with the attention of senior officials.
Bottom-line pressures are mounting in manufacturing industries to reduce the cost of manufacturing with the best quality of products. All areas of the industry are under mounting demand to lower costs and boost productivity.
Manufacturing is no exception, with supervisors and managers spending more and more time finding new ways to cut costs. Particularly important in a manufacturing environment is the overall effectiveness and efficiency of operations. These factors are increasingly scrutinized, but there is still much progress to be made.
Manufacturing companies lose revenue each year due to manufacturing line inefficiencies such as downtime, waste, startup and production rejects, and reduced speed. The good news is that many of these losses can be minimized, if not completely avoided, by focusing on methods to monitor, track, and correct issues as – or before –they arise that is by using analytics to achieve optimum returns on assets. To increase overall efficiency, reduce costs, and maintain competitive position, manufacturers must perform at optimal rates, while maintaining consistently high product quality. This means operating with minimal breakdowns and bottlenecks and, when problems do occur, having the ability to rectify production issues and get back up to speed quickly.
Overall Equipment Effectiveness (OEE) has emerged as a ‘best practices’ methodology for translating the figures from various data sources into a simple set of numbers that enable manufacturers to direct resources toward issue resolution and improved output.
This information is valuable only when used in a timely and informative manner to improve the effectiveness of the entire process. By routing the information through an OEE system for analysis, the efficiency of individual machines, manufacturing cells or assembly lines even entire plants can be monitored, and resources directed to fine-tune operations.

As a result, OEE empowers manufacturing organizations to systematically improve processes and in turn, ensures consistency, maximum quality, and productivity – all resulting in measurable and direct bottom line savings.
OEE targets the most common and critical sources of manufacturing productivity loss and places them into three primary categories – Availability, Performance, and Quality.
Availability compares the amount of time a machine or line should ideally be available with the actual amount of time it is up and running. Performance statistics compare the ideal and optimal operating speeds of line or components. Quality quantifies products that do not meet quality standards. All three factors, and OEE itself, are generally expressed as percentages reflecting efficiency allowing for ease of comparison and improvement measurements. By monitoring the Quality parameters continuously the defect rates can be reduced and which will help in reducing the after sales warranty expenses.
By using OEE to identify inefficiencies and boost capacity on existing lines, manufacturers often find that additional planned lines are unnecessary. By making lines more efficient and freeing up existing staff, a manufacturer might be able to bring on new lines without hiring additional staff.
Not all parts of a manufacturing operation will benefit equally from the implementation of an OEE system, and so the first step in implementing OEE is to determine which parts of the operation would most benefit from OEE reporting. This could be an individual line, a group of equipment in the facility or even an entire manufacturing plant.
OEE dashboard provides detailed analyses of the factors that impact the manufacturing process and contribute to the loss of effectiveness. This level of insight and analysis allow manufacturers to identify and isolate quickly production problems, and apply a solution. By illuminating the sources and causes of downtime from an integrated perspective -- pinpointing production bottlenecks, and identifying quality issues.
Optimized line efficiency, however, cannot be achieved with OEE alone. Continuous line monitoring and control is an ideal way to stop inefficiencies before they happen. Long before a problem manifests itself in the OEE analysis, it occurs on the line. Such problems will, if left unaddressed, ultimately impact line productivity. An integrated OEE system assists in production surveillance provides alerts for incidents that can potentially impact productivity, increases operators’ interactions along the line, and turns raw data into actionable knowledge that boosts overall line efficiency. It is only this combination of OEE analysis and constant line vigilance that can deliver optimal line performance.
With continued pressure on manufacturers to operate their facilities more efficiently, many organizations are aggressively seeking OEE solutions that can be easily integrated with their existing technology infrastructure. In doing so, manufacturers can eliminate issues common to stand-alone solutions while achieving business goals. OEE provides a structured approach for identifying complex production problems, and distills them into a simplified, cohesive set of actionable intelligence to optimize line efficiency. As a result, OEE empowers manufacturing organizations to systematically improve processes and, in turn, ensure consistency, maximum quality, and productivity – all contributing to maintaining a competitive position in a rapidly changing marketplace.
Integrated OEE systems provide an ideal platform for intelligent, real-time reporting of incidents, flexibility of configuration, simplified implementation and streamlined deployment. By the entire packaging ‘ecosystem’ integrated OEE provides a level of clarity that supports root-cause analysis and enables quick decision-making. As such, it serves as the basis of any continuous improvement initiative in the manufacturing organization, and provides an ideal means of collecting information in support of ‘Six Sigma’ or any quality focused program.
Need for the solution- The Way Forward:

The organization can be run effectively with the visibility starting from the shop floor to enterprise. The financial health of an organization is without doubt a vital component of organizational performance. For globally spread organizations, integrating financial information from a large number of physical and electronic sources and plant operation information in real time is extremely challenging. The problem underlying integration is not due to the lack of technology; it lies in the fact that today’s competitive market demands constant ad-hoc adjustment of business processes. When and where these needs arise, is difficult to predict theoretically, but rapid integration of data from dispersed systems is almost always required to support these needs.
Loss in yields, stoppage due to equipment breakdown, delays in setting up the production line and maintenance activity are key factors that affect the overall production efficiency. These factors reduce the production capacities. Lack of understanding of the true performance of the manufacturing units by the plant manager, is the cause for encountering challenges in improving the overall operational efficiency.
Enterprise Analytics Dashboard captures the information in three dimensions; Profit and Loss, Business Flow information and manufacturing related information in a single dash board view. The manufacturing KPIs provide OEE (Overall Equipment Effectiveness), Availability, Performance, Quality and yield with multiple levels of drill down. Profit and Loss related information which captures various KPIs like gross sales, cost of goods sold, sales returns and allowances which will say about the gross profit and also it will provide information on selling expenses and general and admin expenses. The business flow data shows the details of Bookings, Plan, Invoices and Backlogs with multiple levels of drill down either at sales organization or Plant level.
The main intention to build the dash board is to provide a holistic view across the enterprise which helps key stake holders to take strategic decision to enhance the performance of the organization. It is powered with web enabled features to provide access using any web browser from any remote location using PDA, Laptop or desktop. The dashboard is powered with analytics to help management to take decision proactively at right time at right place. The dashboard shows the trend as well as the historical data by using analytics. KPIs are shown using various gauges, graph and tables for easy visualization. The dash board has the alerts capability which will send emails base on the variances to key stake holders to push them to take the corrective actions.

Addressing the Challenges:

This is a framework for addressing the challenges not only from manufacturing KPIs perspective; it also addresses the enterprise financial KPIs as well as Business Flow KPIs. We are here targeting at linking the manufacturing KPIs as well as financial activities and business flow information together which will address the situation more effectively. This empowers C Level executive s to take quick decision. This will be explained in our solution approach section.
The corporate objective is to create share holder value creation and which can be driven by various value components say financial and operational value components. These value components can be achieved by using value drivers as explained in the diagram. Value drivers are driven by the management decision.
To implement this framework the financial, operational and business flow KPIs are required together to bring the insight on the manufacturing organization

The Solution Approach- Enterprise Analytics Dashboard:

Dashboards are visual representations of enterprise performance that integrates a variety of data elements into a single view. Our dashboard combine graphs, tables, and gauges to deliver maximum visual impact in a format optimized for quick absorption and comprehension. Enterprise Dashboard displays data across enterprise using these following KPIs.
• Manufacturing KPIS
• Profit and Loss KPIS
• Business Flow KPIS

Enterprise Analytics Dashboard allows C level Executive to view the KPIs information in a single pane which gives more insight on the enterprise and also address the challenges discussed earlier. This shows the manufacturing KPIs (OEE, Availability, Performance, Quality and Yield Rate), Profit and Loss Visibility and Supply and Demand (related to sales order) in a single view with analytics capabilities. This helps in

• Increased plant operational visibility with all KPIs on one display. No more searching through many Distributed sources.
• Increased awareness of plant operations and profitability due to easy visibility of key performance indicators (KPIs) in a single view
• Supports easier and better decisions with raw data converted into actionable information by the help of analytics which provides not only the past historic data but also the future trend.
• Improved visibility by getting all the information in a single dashboard with drill down view capabilities to locate the root cause.
• Email alerts option in case of variances to respective stake holders and the target can be set at various levels for achieving the best possible outcomes.
In each of these KPIs further drill down is available and a set of reports that allows corporate decision-makers to gain true visibility. The KPIs that can be captured are shown in the below diagram.

Benefits of Enterprise Analytics Dashboard:

The Enterprise Analytics Dashboard provides these business benefits for a better and quicker return on investment.
• Real-time KPIs provides the real insight across the enterprise to have a better control over the enterprise.
• Web-Based capability helps user to access the dashboard from any remote locations.
• Platform-independent data access can easily be integrated to any data source to populate the data on the dashboard.
• Analytics help in providing the business trend as well as KPIs past trend and also helps in predict the future best on the historical data.
• Single site and Multi-site extensibility will support connecting plant and enterprise at various locations.
• Single version of truth for plant OEE, business flow and P&L KPIs will say about the enterprise as and when required.
• It will help in improving quality of the products manufactured by continuous monitoring system which will ensure the right at the first time and can help in reducing the warranty expenses.
• Waiting time for report consolidation can be reduced drastically as everything is available by a single click.
• Continuous monitoring and co relating the expenses which will enable organization to optimize their expenses.
• Better utilization of assets can be achieved by reducing the line idle time and machine downtime.