A. Eschbach, Shiftconnector, Boston, Massachusetts
Plant safety, product quality and efficient operations in oil and gas processing rely on accurate knowledge transfer between teams and across shifts. This is often a manual process, supported by shift turnover meetings, where observations and instructions on opportunities are shared. These in-person conversations are usually supported by written logs, which may be detailed in spreadsheets, documents or a general manufacturing execution system. Other information may be distributed via emails, which can generate tediously long chains of responses that may or may not be pertinent to many of the recipients copied on the chain.
With this approach, important information often falls through the cracks or risks being siloed and not passed along to the appropriate teams. The people who need critical updates the most may not have access to software systems where the information is documented or may need help finding the information specific to their responsibilities.
Oral knowledge transfer can be especially impactful, as people can forget specific details after a long shift or ignore details during a busy shift change. Additionally, critical institutional knowledge can easily be lost when people are absent or leave the company.
Common knowledge transfer challenges for shift handover include creating silos where strategic information is not transferred between teams, and where people may not have access to the systems where data is available. Visibility may be an issue when information can be accessed, but staff may not know they must look for it. Confusion and complexity arise when people do not understand which information applies to them and, therefore, do not know what actions to take.
There is no doubt that shift handovers represent a critical vulnerability for those in the oil and gas industry. In fact, one oil and gas company recorded that 40% of its plant incidents occurred during shift changeovers.1
A digital knowledge center creates a critical repository. The information generated from shift changeovers and other routine activities represents an exceptional opportunity for digital transformation in the hydrocarbon processing industry. However, companies must take a worker-centered approach to digitization to generate optimum results.
An approach centered on people looks beyond digitization, automation and cyber-physical systems to consider the needs of the workers and teams using the tools. For example, what must they know, when is the information needed, and what decisions must be made? Other questions arise, like who else must provide input to facilitate or approve those decisions, and how can staff be empowered to perform their jobs safely and efficiently?
Consider day shift technicians in a petrochemical manufacturing plant. The technicians must quickly know the status of the processes they are taking over from the night shift and exactly what next steps are required at the beginning of their day. They also need to quickly become aware of any problems that require troubleshooting, new directives from management or safety and/or maintenance issues that must be addressed. While some information may be conveyed during the morning meeting, other data is scattered between logs and documents maintained by different people. The shift team must also sort through numerous new emails to decipher what pertains to them and what has or has not been accomplished since they left their shift.
What these shift teams should be able to rely on is an accurate and centralized knowledge repository that collects all the data and observations from other team members. Such a resource provides the information needed for their jobs in a format that is easy to understand and act on. A digital knowledge center acts as a shop floor cockpit, streamlining information collection, and transferring and allowing teams to quickly get up to speed with information relevant to their roles and responsibilities. This cockpit also easily enables people to share their instructions and observations with everyone who needs them across the enterprise.
Connecting workers with a central data repository. A centralized digital repository for data collection and knowledge transfer is transformative for chemical manufacturers. However, to generate the greatest benefits, the system must be built around the needs of the people who will use it. This people-first approach to digital transformation is the guiding philosophy behind Industry 5.0, which focuses on connecting technology with workers to capitalize on the advantages and strengths of each.
Shift management software addresses knowledge transfer problems by eliminating information silos, improving visibility and transparency, and reducing complexity. All personnel receive access to the correct information at the right time to do their job safely and efficiently. This type of software reduces errors related to shift handover and knowledge transfer (FIG. 1).
This centralized knowledge platform allows the people using the platform to help design the necessary automation, enabling them to better adapt to the technology and work smarter. The centralized knowledge platform enables:
Access to real-time information and trends allows managers to address emerging problems and adapt to changing market realities, such as a raw material shortages or a sudden surge in customer demand. Information sharing across teams enables personnel to identify how their roles will be impacted, empowering people to make sharper and more accurate assessments based on knowledge-sharing, which improves plant safety, productivity and resilience (FIG. 2).
Dozens of chemical manufacturers have increased safety and efficiency by implementing worker-centered digital transformation strategies, including addressing critical safety issues. Personnel working in certain facilities have been more disciplined in executing their routine tasks and have communicated proactively about observations. Additionally, workers have been able to better coordinate repairs and other incidents across departments and disciplines. In the U.S., a customer reported increased asset utilization through reduced downtime and fewer performance dips after operators became involved in loss reporting.2
Preparation for the future labor market. While a people-centered approach to digital transformation will help process manufacturers reduce errors and accidents, ensure consistent product quality and maximize productivity, it will also meet the needs of today’s workers. Many plants have lost—or will soon lose—seasoned line workers and managers with decades of institutional knowledge. Fewer young people choose manufacturing as a career, and those who do tend to change jobs more frequently. This underscores just how critical knowledge transfer is to the ongoing health of the plant—not just between shifts, but over time.
A centralized knowledge repository ensures that historical data and important information (e.g., process instructions, safety procedures, maintenance requirements) are preserved as workers change roles or leave an organization. Employers can also get new workers up to speed quicker and maintain consistency in operations. New workers will have easy access to the information they need to perform their jobs well and grow their knowledge and skills. Helping workers become successful and empowering them to take a proactive role in the organization improves job satisfaction and commitment, which helps employers retain and grow the best talent.
The maximum impact from a digital shift handover platform has been built specifically for the process industry and can be configured according to the needs of the workers at each plant. If the company’s plants span the globe, the platform must also be adaptable to specific demographic and cultural perspectives. High user acceptance indicates that workers are allied with the company’s mission to expand its digitalization journey. Therefore, a people-focused approach to digital knowledge transfer will improve the shift handover process and create a stronger, safer workplace ready for the future. HP
LITERATURE CITED