The 80-20 Rule Will Drive Technology Adoption
The 80-20 rule applies to any task faced by manufacturing. True to its definition, there are key areas which should be addressed as a priority.
Vilfredo Federico Damaso Pareto was an Italian civil engineer, sociologist, economist, political scientist, and philosopher. Among his many accomplishments, he is best known in engineering circles for his contribution of the Pareto chart and the 80-20 rule.
Within the manufacturing universe, the Pareto chart predominantly identifies constraints by severity. Scrap by quantity or downtime states by the accumulated duration or by frequency.
In production, the 80-20 rule is used as a prioritization metric for which operational tasks should get more attention based on the return, measured by throughput, delivery statuses, or another critical metric. Each of these tasks produces, in the end, profit for the company. Therefore, the speed with which these tasks are accomplished will ultimately affect cash flow. However, production management is constrained by the assets and human resources on the shop floor. More precisely, the efficiencies of these assets.
Applying The Rule
If one were to step out to work on the business instead of in the industry, they would face yet another level of constraints requiring the same severity categorization. At this level, the stakes are much higher because the direction will determine the wholeness of the business for years to come. Decisions regarding capital spending on facilities, machines and resources, HR investment, supply chain logistics, distribution, etc. A myriad of considerations and issues, all interrelated and vying for attention in the long-term plan and capitalization. When considering manufacturing and the shop floor, one is faced with the capital expense for upkeep and replacement of heavy machinery. What drives the decision to the acquisition of new machinery? Growing service issues, lack of Capacity, obsolescence, inability to control scrap, underperforming throughput, and the addition of automation. Ultimately, these weighted considerations initiate the purchase of costly machinery. However, when these considerations are mapped into a Pareto, what would be considered the obvious response, buying new equipment, may be the wrong decision. For example, if a Pareto showed that a shortage of Capacity was the major constraint to the factors driving profitability, the initial belief is to purchase more machinery. However, this also requires floor space, additional labour and materials to produce more output to meet the capacity shortage and delivery time. A much more viable solution to capacity limitations is a MOMs solution. A ”MOMs,” a Manufacturing Operations Management System, is designed to connect and make visible the shop floor. It will provide analysis tools and real-time alerts to emerging conditions. It will identify constraints and efficiency impairment within the operation. It will support the validation of equipment purchases and determine hidden Capacity.
Employing a MOMs solution costs only a fraction of purchasing new equipment. It requires no additional real estate, floor space or HR resources. Efficiency metrics will prove that all machines on the shop floor only operate at 50% (or less) of their potential Capacity. By employing MOMs, each enrolled machine asset or work center has a real, attainable potential to improve its throughput by 10 to 50%. MOMs will extend the life of all the machinery on the shop floor. It will drive throughput at manual work centers and improve quality and output. The same MOMs deployment will also validate when equipment is no longer viable. It will validate the purchase and deployment of automation. It will capture operational tribal knowledge before it disappears. It will also prove that the plant is not performing as well as reported. It will make some people nervous because it will threaten the status quo. The same system can validate new equipment purchases by providing a baseline throughput compared to vendor-specified performance estimations. The data will help establish the adoption of new manufacturing processes, such as additive machining.
Coming To Terms
Industry 4.0 is here to stay. The inarguable proof that performance, availability, and quality can all be improved through accurate data should be the motivating factor in pursuing a highly cost-effective method of supercharging the shop floor and bringing accountability to the operation. Yes, you can work on 80 percent of the issues, which will garner a minimal return, but the top 20 percent will reap the most significant value for time, money, and effort. The top 20 percent should never be myopically addressed through expensive CapEx acquisitions. Rather ongoing technology adoption will make each process on the shop floor accountable. Throwing mud at the wall to see what sticks, the accepted method of operation, can no longer be considered viable. Rising costs have seen to that. With a rapidly shrinking pool of skilled talent, adding people to boost operational efficiencies is not an option. The opposite is true, whereas manufacturers are trying to move toward entire automation/lights-out operations. But that is prohibitively expensive and is not feasible in all areas. An aggressive move to consolidate facilities to reduce operational and logistic costs adds even more stress on existing operations to produce. Old thinking has value but not when used as a barrier to modernization. As younger, more tech-savvy managers become, senior, technology adoption will become easier. Technology has two ditches into which prospective adopters can fall. The “easy to use,” simplistic monitoring systems, which are SaaS with never-ending costs, are guaranteed to leave many users with a bad experience because data appears wrong or there is no flexibility in the system to meet a manufacturer’s unique requirements. The other ditch is full of stalled, costly, poorly manned projects based on “build from the ground up” tool sets requiring months to deploy with services in the 5x range of software cost. Most of such systems are thinly veiled SCADA systems looking for a new lease on life in a new market. Even when a system in this ditch is finally deployed, it’s a snowflake that will require expensive ongoing services. Otherwise, it will be obsolete quickly because it is, by design, inflexible.
Bringing It All Together
Similarly, as subject matter experts in a company evaluate every technology employed in new hardware, equipment and automation, the same level of scrutiny should be used in selecting a MOMs system. A manufacturer would never put all their eggs in one basket, purchasing a massive do-everything machine to fulfill completely different operational functions, yet, they look for the one-size-fits-all ERP, MRP, MES, MOM solutions because they think that bolt-on software added to what they already bought makes things easier. Rarely does the do-all software even remotely deliver on its promises. Finally, even when a good prospect for a MOMs solution is found, one critical aspect, if not addressed, can cause the project to fail. Accountable champions.
In the same way that a company will hire capable, skilled operators to run the latest additive manufacturing systems, they need to select and even hire a qualified person to champion MOM integration and use of the MOM system. A good MOM (Manufacturing Operations Management) system ties in the collecting machine and work center operational events, operator interaction and ERP job data. Three converging data streams. The champion needs committed resources from engineering, QC, maintenance, operations and rank and file. He needs to be qualified in Continuous Improvement methodologies or have help at his disposal.
In the end, Pareto expects us to focus on the top 20 percent. That would be issues, plans, projects and technology that improve throughput, delivery and profitability. The personnel in each area, department and shift must be taught to look at everything to improve it. Everyone can contribute from poke-yoke, Gemba, Kaizen, Kanban, material acquisition, resource management, and machine and technology adoption. But the most significant impact now and in the future is the accurate, actionable data from the three convergent data streams to make critical decisions. Decisions to adopt manufacturing methodologies, hire personnel, consolidate resources, and validate equipment engineering and buying decisions require data. A MOM system is a manufacturer’s best friend when correctly chosen, deployed and managed.