To be competitive in today’s dynamic manufacturing environment, small- and medium-sized manufacturers (SMMs) need to implement mechanisms to facilitate the effective processing of multiple streams of highly volatile and time-sensitive customer requirements. This allows SMMs to provide truly agile performance and to leverage previously opaque data to promote efficiency and economies of scale. It is made possible by implementing digital tools, processes, and systems powered by data science and advanced algorithms, ensuring data is quickly and accurately received, interpreted, and deployed with minimal human intervention.
But SMMs face a lot of potential hurdles, which are highlighted by the Interdisciplinary Center for Advanced Manufacturing Systems in its new Smart Manufacturing Adoption Study. Barriers include little awareness of available technologies, few relevant business cases, limited access to capital, perceived costs, an inability to find technical resources, and a capable workforce with the required skillsets. Many manufacturers believe they are digitally transformed by introducing Industry 4.0 technologies such as cloud computing and artificial intelligence, but these are better described as discrete elements of a digital transformation. When executing a comprehensive digital transformation, it is just as important to focus on the digital ecosystem that fosters end-to-end transparency through data connectivity and interoperability.
Common perceptions of the impediments to the adoption of the digital ecosystem include misconceptions about the complexity of the process. However, digital technologies can simplify many operations and provide the structure and information flows to significantly improve performance metrics.
Despite the barriers, some SMMs have found successful ways to use and leverage digital capabilities to transform their operations and address these issues to become more agile. An example of this is Laser Precision Inc., a full-service sheet metal and plate fabricator in Libertyville, Illinois.
Recognizing the importance of being able to handle vast amounts of demand data as a supplier to a global OEM, Laser Precision began its digital transformation. Since 2004, the company said it has increased total part count thirtyfold, while improving quality performance to less than a 100 parts-per-million defect rate and achieving an on-time delivery percentage of 99.92 percent. Laser Precision accomplished this with 13,000 part numbers while processing an average of 2,000 order changes daily. Despite such dramatic increases in capacity, performance, and agility, the company hasn’t had to increase administrative staff. Such results are facilitated only when information flows are automated and understood, allowing digital systems to process vast amounts of information while administrators focus on exceptions and opportunities.
As OEM sourcing strategies became more complex, Laser Precision recognized that its inability to effectively process customer requirements constituted a significant barrier to growth. The company correctly anticipated a subsequent increase in parts per vendor, total shipments, demand volatility, a greater need for agility, much more performance scrutiny, and an overall reduction in lead times. As a result, Laser Precision transformed its entire business model by engaging with an enterprise resource planning (ERP) provider to develop an interactive system to act as a conduit for information, not just as a reporting tool.
Key components included:
Increasing the ability to track, understand, and synchronize changes to customer demand with production capabilities and capacities across the entire value stream;
Providing employees with real-time information to respond quickly, efficiently, and accurately;
Matching and updating the ERP system every 90 seconds with the latest information regarding current demand and supply elements; and
Automating and orchestrating the value stream from demand and procurement to scheduling and fulfillment.
Laser Precision began to bridge the gap between itself and world-class OEMs by managing volatility, obtaining an information-centric business model, maintaining consistent quality performance, and turning chaos into conformance.
Though every company faces unique challenges, several lessons can be taken from Laser Precision’s experience. The following takeaways are enablers that other SMMs can implement along their path to digitalization.
The goal for manufacturing support systems, such as ERP software, should be to provide the right data, at the right place, at the right time, and in the right form to make the best possible decision. Achieving this goal requires an information-centric business model in which data is accurate, current, and, therefore, trusted. It must be the central nervous system of the business and function not only as the repository for key manufacturing elements but also act as the deployment infrastructure. For this reason, the ERP system must be customized for users and their business.
Often the data elements act as guarantors of performance, ensuring certain operations and functions have been completed. Only through synchronizing with internal processes can the data system act as a performance gate, ensuring actual operations have met processing requirements. Developing a support system that can handle extreme volatility requires a holistic view of the full manufacturing ecosystem and an understanding of how all components interact. Support systems must synchronize all elements required to manufacture a part with cascading impact. For example, when a new order enters the system or if a change is made to an order, material, labor, and capacity are all automatically adjusted accordingly in rapid succession. These codified responses are made possible by standardized demand streams, which allow the manufacturing support system to use its codified rules to update the necessary data elements.
Laser Precision saves all information for one part in a centralized location, under an electronic demand profile (EDP). The EDP contains information for one part for one customer, including all technical data required to manufacture a part: models, drawings, machine programming, bill of materials data, work instructions, quality documents, and routing information. Having all part information in one location as the single source of “truth” eliminates the possibility of having duplicate data that doesn’t match. A crucial element to the configuration of Laser Precision’s EDP is treating all new parts and revised parts as new parts. Doing so permits all EDP data elements to be updated when a revision is made. The part takes on a new identification number that denotes both the original part and its revision. Therefore, the revised EDP is referenced, and there is no possibility of producing a part to the wrong revision.
By automating the system response to volatile demand requirements, Laser Precision minimizes the need for costly manual intervention, which is error prone and delays timely data. It isn’t essential to acquire one catch-all software to support the manufacturing system. However, data must be combined so the aggregate output is accurate and updated in near real time. The value stream must respond to fluctuations in demand, change orders, and unexpected drop-ins automatically throughout each part’s lifecycle: procurement to production to fulfillment.
“Any value stream only works if all parties are planning with the most current information,” Laser Precision President Jeff Adams said. This requires that internal and external data such as customer demand accurately match production status and capacity. Highly volatile demand streams make this seem daunting; however, a computerized system with codified responses can update all necessary data elements with ease when utilizing a standardized format for receiving data.
While scheduling can provide important information about macro business requirements, such as capacity, staffing, raw materials, and MRP in a volatile environment, prioritization fosters agile processes without transferring the chaos and volatility of the raw demand stream. Once a sequence is determined, the schedule can be generated in a simple, automated way. It isn’t that a schedule doesn’t exist, but rather the schedule is fully determined by priorities. SMMs can implement an automated sequencing algorithm that requires little to no manual intervention, which is key to on-time delivery and cutting costly non-value-added activities. Manual interventions should only be focused on exceptions and opportunities, therefore reducing workforce costs previously spent on redundant tasks that are better performed by the system.
Laser Precision regularly updates in-process status to keep pace with actual production. The operators could receive an updated screen with the newly ordered set of priorities, eliminating the uncertainty of the current orders and allowing for the support system to adjust completion dates according to manufacturing fluctuations. Updating the production status allows the enterprise support system to reorder priorities based on completed work.
Each operation will continue running based on set priorities, which will update as higher priorities enter that operation’s work in progress. It’s a continuous loop—the system feeds priorities to the plant floor, which tells the enterprise system the production status so that the priorities can be updated.
Laser Precision repurposes employee time that was once used on manual intervention to focus on exceptions and opportunities. Instead of every demand stream requiring manual intervention and scheduling, only exceptions, such as drop-ins or last-minute demand, are handled by a person. Laser Precision recommends using a time fence for exceptions. In other words, they allow (almost) all demand changes until a specific time frame. That way, chaotic demand streams are not allowed to affect production on the plant floor. Changes that are outside the time fence are accepted/declined automatically based on capacity and material availability.
Exceptions are changes that are requested inside the time fence that require review and collaboration for resolution. In this case, an employee has to make a decision that the computer could not make. This frees up employee time to spend on forward-thinking opportunities, envisioning further improvements that will enhance the digital transformation and overall data ecosystem performance.
Ultimately the goal is to digitalize and automate the entire value stream to make the best possible decision. Every step in the production process—incoming demand, procurement, change orders, and fulfillment—should be entered, modified, and executed digitally, with human intervention limited to exceptions and approvals. This allows Laser Precision to focus on continuous improvement, saving the company from a “tyranny of the urgent” approach that stifles growth and innovation.
Contributed by Ashley C. Yarbrough, a Ph.D. candidate and graduate research assistant for the Interdisciplinary Center for Advanced Manufacturing Systems at Auburn University, with Daniel F. Silva, an assistant professor in Industrial & Systems Engineering at Auburn, and Morris Sneor, vice president for Paradigm Productions Inc.
For information about Laser Precision visit laserprecision.com or call 847-367-0282.
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