Tracking Shop Productivity and Gathering Information

A relational database is the ideal solution for fragmented data collection and storage, says TrueLogic’s Ellen Sellers.


Facebook Share Icon LinkedIn Share Icon Twitter Share Icon Share by EMail icon Print Icon

Q: Our shop is looking for ways to track productivity and gather more information on our operations. What steps should we take to institute that?

A: Although companies involved in the wet process manufacturing arena may believe that lagging production efficiencies and effectiveness result from a lack of data, this is generally not the case. The plating/finishing industry, like most manufacturing industries, generates a plethora of data. A common problem is the data is created in many different forms and located in many different areas. Data formats can range from handwritten notes to paper log books to Word documents to Excel spreadsheets. The data is compartmentalized in silos that do not lend themselves to utilization. The wet process laboratory, production floor, and process engineering and quality departments, as well as purchasing, have key performance indicators that would benefit greatly if the data generated from each area could be entered into, stored and accessed from a central receptacle.

The ideal solution for such fragmented data collection and storage is for each area to enter data into a relational database. Once the data has been entered into such a database, it can be processed and turned into useable information. A relational database can process each new data point individually and/or collectively with existing data. It can then use the resulting status/relationships to maximize the accuracy and consistency of the processes being monitored and, ideally, control these processes to the highest level possible.

A tightly controlled data collection structure gives companies a tool with which they can minimize waste, including problems resulting from multiple entries of the same data into different areas or systems and the problematic errors that quite commonly result. Using a well-structured relational database can significantly reduce the number of potentially catastrophic inefficiencies and risks associated with human-machine interfaces (HMIs); these have been identified as being among the key problem areas when audits reveal irregularities and inconsistencies in controlling manufacturing processes.

But a relational database must be easy to use, involving simple data entry, configurable analysis screens and status reports, and provide interactive feedback. With the correct structure and presentation, these advanced tools invite and encourage extensive utilization, from initial data gathering and input through multiple layers of data mining, engineering, quality assurance and reporting.

The improvements in data gathering methodologies and information utilization can result in significantly increased consistency, which allows manufacturers to reliably manage quality.  Another quite significant benefit of the improved process control via consistency is providing manufacturers the oversight necessary to create objective evidence for process improvement as well as easing audit preparation, actual audit activities and, ultimately, audit results.

Having a central receptacle to store documentation and media associated with processes, tanks and testing will create consistency among people, shifts and facilities. With easily accessible standard operating procedures, test procedures and training material, manufacturers have the flexibility to make changes in a centralized location and know that every stakeholder will be using the same, up-to-date information. 

The implementation of such a system should be performed by a team possessing process knowledge and the talent to implement standard operating procedures. This generally includes individuals who, over time, have obtained tribal knowledge resulting in best practices, and who have the ability to directly or indirectly transfer that knowledge to the centralized receptacle for storage, protection and utilization. 

Traceability is another very powerful attribute of a relational database. Information in the system is not stagnant. It can make manufacturers aware of the current state of critical areas of the operation, but it also offers information about how the operation arrived at that current state. Data can be tied to a person or persons, times, and locations. The system can provide heightened awareness around specific data, allowing the opportunity to address oncoming issues before they become problems—to become proactive instead of reactive.

Once the best practices have been implemented and moved into a system, and the organization is reaping the benefits of increased consistency and improved quality, then data collection, data input, data processing, data analysis and resulting actions may benefit from being automated. However, it is critical that the team(s) in charge of implementing and operating the system possess a solid working knowledge of the process or processes before automating, because automating a system that is not well-understood can lead to exacerbating problems associated with the processes. Successful automation can allow companies to further eliminate inconsistencies and mistakes that cause reworks, rejects and recalls by eliminating more source-point HMIs.

Finally, evaluating and adjusting operations can be streamlined by using scheduling options developed within a relational database. Whether a company is operating totally manually or has implemented differing levels of automation, having the ability schedule and monitor activities can allow it to fully maximize efficiencies and resource allocation effectiveness.  Setting start times and allotted times for completing specific tasks, from testing to preventive maintenance activities, allows for exceptional utilization of time and materials while providing the consistency necessary to manage quality.

It is worth repeating that almost every form of manufacturing creates a significant volume of data. The difference between ongoing frustrations inherent in chasing quality using raw data and the success that can be achieved by utilizing a data repository with the ability to turn that data into useful information is an absolute game-changer.

Ellen Sellers is with TrueLogic Co. Visit truelogiccompany.com.