The Origin
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.
Annual General Meeting 2023
/in Events, Recent News/by Rashi RathoreWhy do you need a monitoring system?
/in Blog/by Tim SmithWhy do you need a monitoring system? The most obvious and usually the initial reason is real-time visibility and utilization measurement. That is what most of the monitoring systems espouse doing. Let me qualify the statement. In the most basic configuration with machine-only reporting, the results are long and /or frequent IDLE conditions. Basic utilization as a percentage and real-time “uptime/downtime” visuals. This approach falls short because there is no easy identification of the root cause of IDLE events. Furthermore, the possibility of serious false-positive events is likely because circumstances or conditions, if tracked, would likely identify scheduled breaks, meetings, setup time, change-over, material conveyance, missing personnel, etc. These lightweight and cheap monitoring systems are simple to employ but lose value once running for a while. Furthermore, most are in the cloud, introducing latency and data security issues. The next level of monitoring supports an operator interface for interaction with the system. Most interfaces allow for an operator to classify an unknown downtime event. This adds granularity to downtime to better assist in root cause analysis. However, such a feature available across the host of monitoring packages has no consistency of options. Whereas some have a set or a limited number of reason codes, others are extremely flexible in providing custom reason selection for each machine to match the operation type. Issues arising on a laser are far different than issues arising with welding or on a press or multi-spindle CNC. Other more sophisticated HMIs provide advanced features such as ticket generation, checklists, work instructions, operator-guided e-alerts, operational triggers, barcode support, history editor, real-time commenting, etc. (MERLIN). Then the ability to manage jobs or OpSteps further separates the field. Recording activity against a job or OpStep is critical for any facility, especially for Job shops, mould shops, prototyping shops, or high-value, low-volume shops. If a shop collects shift utilization without job information, it is unlikely that job and shop-related events are correctly recorded and classified as negatively impacting utilization. Adding jobs or OpSteps into the monitoring system introduces the performance metric, which is key to throughput measurement. Just because a shop minimizes downtime doesn’t automatically improve all aspects of the operation. How fast a machine runs and whether it’s producing quality parts is just as essential. Does the system employed support true OEE based on product standards, cut time and material conveyance time rather than just “Cycle” time? Does the system employed provide for both good parts and reject part categorization? Does the system employed support operator login and logout, non-machine-related activity, and operator-centric metrics? This level of event collection is not found in cheaper, low-end products. Ultimately, the system should be more of an operations management system that leverages custom event types, such as machine overrides, follow-on automation and robotics, and inferred machine events, such as starved or blocked. It should employ triggers to infer conditions, manage output, alert teams, send or retrieve data from other systems, and be future-proofed to expand its function, features and integration across the enterprise. Finally, a system must be easy to roll out. Simple to connect assets, flexible enough to represent information unique to the operation. It must provide tools for production, management, supervision, engineering, Quality Control, and the operator on the floor. The latest recommendation from cyber-security firms is that such systems should reside within the organization’s four walls and not expose the company or its data in the cloud.
The emerging consensus is that entry-level, SaaS-based monitoring systems need more flexible, accurate, and resolution tools for operational issues. A good operations management system connects the floor quickly and effectively. It provides an accurate real-time data flow to the corporate monolithic enterprise tools through real-time subscription to integrated OPC UA servers. Such a system is the perfect production tool and middleware for an organization.
You do not want to be the person who selected a solution based on price or perceived ease of use. As discussed, these usually fail to address an organization’s issues. Nor do you want to be the person who followed the market speak and bought into a large toolkit approach which requires 5x services, custom programmers and months of integration to produce even the simplest of feature sets. Nor do you want to be the author of a skunkworks internal development that drains resources while recreating the wheel for the nth time, only to once again be orphaned as resources move on.
MERLIN Tempus can deliver all of the features and functions described. It can be rolled out with a fixed-price project with rapid deliverables. It can connect to ANY machine or operation. MERLIN can save stalled or failed projects from monolithic systems by providing simple connectivity to all machines and operations and serving them up to the enterprise system.
Ultimately, you are the one who can articulate what your expectations are for any system. But any system worth considering must provide information for the following:
If you keep these points in mind, you will not stray from an excellent Manufacturing Operations Management system (MOMs)
The Sad State Of SaaS
/in Blog/by Tim SmithWeighing the options is not always easy.
Centralized hosting of business applications dates back to the 1960s. That was back when users would pay for computing time on mainframes.
In the nineties, we saw the introduction of ASPs, Application Software Providers. ASPs mandated maintaining a separate instance of the application for each business. About a decade ago, mainstream SaaS providers appeared with multi-tenant deployments where users “shared” the computing environment. A key driver of SaaS growth is SaaS vendors’ ability to provide a competitive price with on-premises software. This is consistent with the traditional rationale for outsourcing IT systems, which involves applying economies of scale to application operations. Unfortunately, in retrospect, outsourced IT and SaaS still need to fulfill their promises.
Almost everyone can attest to the frustration of outsourced IT, especially when the technical group is not even on the same continent. Additionally, the faceless outsourced teams need to relate readily to the culture of the users. Similarly, SaaS providers provide a barebones support offering to facilitate their SaaS service. The application is hosted centrally, so the provider decides and executes an update. SaaS providers will upgrade software on a regular bases to address one user group at the expense of impacting all users. Since the service is in the cloud, users who want to work offline with their data face the potential of expensive egress charges. If the data accumulated by the users grows beyond the typical SaaS allowed size, then data storage costs are applied to the user. If the scope of the application grows, such as incorporating more connected devices and more data per device, then initial costs can also escalate. The application vendor has access to all customer data, and in notable cases recently, they have been selling metadata collected from their customer base. The application only has a single configuration, limiting the software’s ability to fit obvious unique conditions in almost all organizations. When a SaaS is considered the route for connecting machine assets and workstations on the shop floor to collect real-time streams of critical data, potential issues around latency, bandwidth, and saturation all come into play. An organization needs redundancy for their internet connection to ensure critical data and functionality can be recovered with the interruption of internet services. If operator interfaces are being used, then typical delays of one to ten seconds can occur between machine-generated and operator-generated data.
The most apparent failure of a SaaS approach is the ongoing service cost year over year. Where most perpetual licensing costs are absorbed over a short period, the year-over-year costs accumulate and ultimately cost the organizations far more than an on-premise deployment would have cost.
Some vendors, like Memex, can provide their onsite deployment as a Capex, leased, subscription, or convertible subscription so an organization can get the best of both worlds. One major challenge to SaaS solutions is the loss of service and data if the provider becomes insoluble and goes out of business. All the investment, procedural changes, time and data, not to mention all of the cost, vaporize. At least with an on-premises solution, the system stays intact and running. In manufacturing, fifty such vendors have disappeared over the last five years.
SaaS has attractive benefits and may be suited for ERP and other low-transaction applications. Still, there may be better options than SaaS when real-time critical data is essential. The disadvantages of SaaS (such as lack of control) are considerable and should not be ignored.
MERLIN can help you with your personnel challenges
/in Blog/by Tim SmithIt is a common complaint that personnel shortage impedes operations significantly.
Retirement transitions tribal knowledge out of the company. The loss of tribal knowledge disrupts operations.
Personnel leaving for other positions. Whether the personnel are team members with time vested in the company or relatively new hires transitioning through your company, both wreak havoc on maintaining a competent workforce on the shop floor.
Everyone would agree that there is a dramatic shortage of skilled labour in the current market. Operators with experience in machining, setup, inspection, tooling, etc., are hard to come by, and poaching other companies’ personnel becomes commonplace.
The critical challenge is that the availability of skilled labour is shrinking, and the availability of experienced management, engineering, and QC technicians is not keeping pace with demand.
What technologies exist today to help reduce your reliance on human resources? New machinery and automation, including robotics, can drive unattended manufacturing where it makes sense. Augmented reality can drastically reduce dependence on skilled labour in assembly and fabrication work-centers. New CI tools can minimize reliance on engineering expertise to drive manufacturing efficiencies, throughput, quality, and delivery.
Aside from the cost, the challenge to adopting and implementing new technologies is the ability to assess its successes to qualify for wholesale adoption.
How does MERLIN help to mitigate these critical challenges? MERLIN connects all operations on the shop floor. Machines, cells, FMS systems, production lines, fabrication cells and work centers. It connects and enables operators, supervision, management, engineering, and QC through unencumbering technologies. It adds value without impact to strained resources.
It provides targeted feedback on constrained resources so you can focus your limited human resources on the most beneficial corrective action. In addition, MERLIN provides real-time alerting to emerging trends and disruptive events so that you can effectively marshal your people.
MERLIN provides product-specific work instructions for operators at the machine where they need them. Access to up-to-date, accurate electronic instructions generated by any world-class documentation system and routed by MERLIN. Such documents as work instructions and drawings.
MERLIN provides ongoing feedback through checklists to guarantee adherence to procedures. MERLIN partners with and integrates Augmented Reality systems like Arkite to provide operator guidance systems, electronic guided training, QC process adherence, reducing assembly errors, enforcing procedures, and instructing new personnel through integrated partnerships.
MERLIN provides critical operational, maintenance, and quality metrics to baseline and milestone your improvement initiatives.
Through innovative continuous improvement tools, your engineering and QC teams can do and achieve far more with fewer personnel.
All levels within the organization have accurate shop floor information through the automated generation and delivery of critical operational reports.
MERLIN support “lights out” production by monitoring and alerting key personnel to any deviation from the operational process. MERLIN can monitor and respond to issues in complex flexible manufacturing systems, nested lasers, multi-axis machines, welders, robotics, and any other processes on the shop floor.
MERLIN can assist in validating new processes and introducing new machines, equipment, and follow-on automation, catching unseen anomalies before they are adopted as part of everyday work. In addition, MERLIN can provide rapid feedback to determine if the planned output matches the actual output.
MERLIN supports integration to your ERP system for pushing work orders, jobs, and product standards into the MERLIN for accurate job tracking on the shop floor. In addition, metrics can be used to calculate capacity availability to validate scheduling and resource planning.
The critical data from MERLIN will provide value in production-costing by identifying lost production dollars and poor performance and utilization.
MERLIN comes as a fixed-price project with rapid deliverables and unlimited user configurations to support how you do business. In addition, MERLIN can be rapidly deployed for quick ROI.
For the foreseeable future, we will experience human resource shortages. You can leverage the most out of your personnel by employing MERLIN without adding stress. You will foster a team approach with healthy competition. In addition, MERLIN will provide a skill-levelling process by which you can improve throughput and quality even in the face of human resource challenges.
The 80-20 Rule Will Drive Technology Adoption
/in Blog/by Tim SmithThe Origin
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.