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Figure 1. A plant manager might be intertested in an overview of how each line is doing (top), while a line manager may need an overview of each machine in the line.
Figure 2. The Pareto is one of the most useful tools for attribute data.
Businesses are buried in data. To begin with, each has a financial reporting system—a federal requirement. Many also have sophisticated ERP systems to drive production and manage inventories. Some collect manufacturing and quality data electronically for compliance or control issues. A few may have a Computer Maintenance Management System (CMMS), managing spare parts and dispatching resources. PCs throughout the company are full of homegrown spreadsheets and databases, tracking metrics related to a department or an individuals responsibility.
Since data sources in the business are not integrated, the data often have discrepancies. Each data source may have limited access for political, compliance or other security reasons. Most of the data is only available in raw-number form, distributed on several reports and screens. Is it any wonder it is difficult to get the management team to agree on potential investments or process-improvement actions?
The equipment used in modern metalworking and fabricating plants incorporates advanced CNCs, PLCs and PCs capable of collecting data on every part of the process. Collecting the data is only the first step in producing insightful, actionable information. Integrating business systems, quality systems, production systems and maintenance systems with powerful analytics is a game changer for most businesses.
What a business needs is one insightful version of the truth, unbiased by manual data entry or political concerns. Data elements become information that drives action and justifies and prioritizes investments.
Too Much Data, Too Little Information
Businesses collect an overwhelming amount of data, both in corporate-supported enterprise systems and in individual files stored on local PCs. The data are stored in a variety of formats including enterprise databases, proprietary application databases, data warehouses and any of the several spreadsheet or personal database formats.
Resources are wasted in most companies producing stove-pipe data analysis, because corporate systems are focused on financial analysis and inventory management—not on operational excellence. The financial data information is very sensitive, so enterprise systems reasonably limit access. ERP systems are very complex and a user must go through extensive training to become proficient at data mining.
The casual user finds it very difficult to mine data from corporate systems. The data required are often provided on multiple screens or reports. Creating custom displays or reports requires specialized programming skills and security authorizations. Requests for IT to produce custom reports for a single department or individual cannot compete with the needs of multiple users that can deliver a higher potential return on investment.
Some businesses have recognized the problem and have created data warehouses to provide easier access to critical operational data, but these are often focused on customer self-service or sales-related issues. However, little valuable data become available for manufacturing.
The material-push modules of most ERP systems are not as valuable in today's just-in-time, high-volume, high-mix production systems. They typically create production requisitions and manage finished goods inventory, and totally ignore the operational details between the two events.
Purpose-built manufacturing applications are rarely integrated with the ERP system. Requisitions are printed and entered manually into the manufacturing system, or electronically copied and pasted. Finished goods inventory is keyed back into the ERP system at the end of the manufacturing cycle. Most shop-floor systems focus on production tracking, allowing manufacturing to answer the question "where is my rush job," but do little for operational excellence.