Name Anil Kumar Joshi

Roll No. 520949950

Course & Semester Master of Business Administration – MBA Semester 4

Subject Name & CodeOM0006 – Maintenance Management Book ID: B1148

Assignment No. Set – 1 & 2

LC name & Code NIPSTec LTD. 1640

Date of Submission 14.05.2011

Session

Assignment Set – 1

1. Preventive Maintenance is an approach developed to reduce the likelihood of the failure of critical equipment to the minimum possible. Elaborate with an example.

Sol:Reducing Risk without Wasting Resources: Doing Risk Management Right Using ISO 14971 can help companies make risk management the core of medical device development.

ISO 14971, “Medical Devices—Application of Risk Management to Medical Devices,” was first published in 2000. The risk management standard radically changed the process of understanding and controlling the risks associated with medical devices. In doing so, it presented a significant challenge to manufacturers. However, too often risk management was treated as yet another box to be checked. When that happens, this invaluable thread that can tie the entire life cycle together, dramatically improve productivity, and, most importantly, ensure the safety of the devices we produce, becomes a drain on resources dreaded by members of the design team and a potential source of failed audits. If the announcement of a risk analysis meeting elicits groans and excuses for not attending, the company's risk management process is probably inefficient and very possibly does not comply with the standard.

 It would be a mistake to assume that risk management procedures comply with the standard just because a notified body or other auditor has not issued any findings. Just like manufacturers, auditors have been and still are learning what ISO 14971 requires over time. However, those auditors have been exposed to the best and worst of what risk management can be. Due to this exposure, auditors expectations of an ISO 14971–compliant system are increasingly more rigorous. To stay ahead of those growing expectations, it is critical to understand the intent of each element of risk management and how those elements provide value to the rest of the development, production, and postproduction processes.

As a first step toward achieving that level of understanding, this article looks at the process of identifying hazards, estimating the associated risks, and controlling those risks to acceptable levels.

Identification of Hazards

One of the most common sources of confusion is misunderstanding exactly what constitutes a hazard. Hazards (as defined in ISO 14971 and ISO/IEC Guide 51) are potential sources of harm.2 Too frequently, the resulting harms are included in the list of hazards. Blending the cause with the result can lead to significant confusion as the process continues.

Hazards include types of energy such as potentially harmful voltages, excessive heat, or masses. They can also include circumstances (called hazardous situations in ISO 14971) such as chaotic environments or operation by untrained or poorly trained persons. None of those hazards, in and of themselves, necessarily results in harm. But each under the right circumstances (trigger events for the purposes of this article) can become sources of injury.

 Unfortunately, too many manufacturers ignore what should be the primary source for identifying hazards: product safety standards. Too often, product development processes simply

treat standards identification and compliance as another task that needs to be done without thought of the purpose or value.

 Device safety standards are critical throughout the risk management process. They identify commonly recognized hazards associated with medical devices. They may identify hazards related to general categories of medical devices. For example, IEC 60601-1 identifies hazards associated with most electrically operated medical devices.3 In addition, standards may identify hazards associated with specific technological aspects. The ISO 10993 series identifies and guides in the evaluation of biocompatibility hazards.4 Others identify hazards associated with specific types of devices. IEC/ISO 80601-2-30, for example, identifies hazards associated with automated noninvasive sphygmomanometers.5 Failing to use such standards as the primary input to the risk management process increases the probability that hazards might not be identified. It can also cause manufacturers to ignore the primary set of risk-reduction techniques (also contained in those standards).

 Hazards alone do not have severities —injuries or harms do—and hazards don't have varying levels of likelihood. Hazards either exist for a device or do not. A hazard becomes a harm when a trigger event occurs.

 Severity Estimation

As a rule, once the potential sources of harm (i.e., hazards) have been identified, determining what harms they can cause is noncontroversial. What is important to remember is that different trigger events may result in different harms (even for the same hazard), and trigger events frequently can cause different levels of harm, each with its own likelihood. For each specific trigger event, it is usually possible to identify at least one harm and severity. However, different trigger events for a given hazard may well result in more than one harm or severity.

 Although identifying harms and their severity does not, as a rule, lead to disagreements in a risk analysis meeting, they can. Most often, such discussions center around the possible severities that can result. If a single trigger event could cause various levels of harm, the most severe should be selected because it would carry the greatest risk (since the trigger event determines likelihood, which would be constant).

 In the end, the decision to add another line item in the risk analysis should be based on whether each harm would have an independent mitigation or risk-reduction technique. If a risk does have a different mitigation, it should be addressed separately.

 Finally, although reaching consensus on the harms that could occur and the associated level of severity is not difficult, it is wise to involve a clinician for validating those determinations. Clinicians are also invaluable in understanding the use environment and how medical personnel are likely to interact with the equipment, both of which are critical to usability engineering.

 Likelihood Estimation

 Those familiar with the most recent edition of ISO 14971 will note that the term likelihood has been replaced by probability in the standard. However, using the term probability in the context of risk estimation can be dangerous because it implies a level of detail and accuracy that simply

cannot exist. Even if it were possible to accurately calculate the probability of a given harm, when a value was assigned (such as a number between 1 and 5) or the appropriate column or row of a risk threshold table was identified, that accuracy is lost.

In short, quantifying whether a harm could occur is always an estimate, and the term likelihood better reflects the fact that it represents an estimation. Spending significant resources to achieve high levels of accuracy with high confidence intervals is almost always a waste of those resources. Therefore, for purposes of this article, the term likelihood is used as a reminder that we are making educated estimations.

For every identified potential source of harm (hazard), there are typically multiple trigger events that could bring a hazard into contact with a person or cause a hazardous situation. Any potential harmful voltage or chaotic environment could cause a person to make an error. In either case, the result could be an injury (harm). For example, trigger events that would cause potentially hazardous voltages would include the following:

An exposure of these voltages such that they can be touched. A failure of insulation. A spill of conductive fluids. A high leakage current (unintended flow of electric current).

Therefore, for the hazard of “potentially harmful voltage,” the risk analysis would branch out to identify each trigger event that could lead the voltage to cause harm. Although trigger events can be identified using any number of techniques, a variation on failure mode analysis can be one of the most useful.

While failure modes and effects analysis (FMEA) should never be used as the primary risk analysis tool, by definition, parts of that process are ideal for identifying failure-related trigger events. Traditionally, FMEA focuses on the failure of component parts of the design and identifies the resulting effect of the failure. Failure mode effects and criticality analysis (FMECA) adds the ranking of the effect in terms of severity or importance. However, in using failure mode analysis as an input to risk analysis, the resulting effect of the failure and its criticality are identified in the risk analysis. So the analysis used as an input to that process need only identify the trigger events (although they can be identified here and transferred into the risk analysis). Failure mode analysis can be applied far more broadly than simply looking at component failures.

However, even though the process of identifying trigger events can be modeled on a traditional FMEA, caution is strongly advised. By its very name and traditional application, an FMEA implies that only failures are identified. ISO 14971 clearly states that harms that result from normal operation of the equipment as well as those caused by failures must be identified and the associated risks mitigated to acceptable levels. Do not allow the similarities between a trigger event analysis and a traditional FMEA to lead the risk analysis team to focus on failures alone.

Trigger event identification (using a failure mode–type analysis) can be applied to more than the device's hardware. It can also apply to software, user interfaces (foreseeable misuse), the environment in which it will be used, manufacturing errors, poor maintenance, misleading marketing information, or even statements by salespersons. In short, all trigger events that could result in injury need to be identified, and trigger event analysis can be applied to each hazard

category. Making hardware, software, usability, manufacturing, maintenance, marketing, and sales as part of trigger event analyses is a way to organize the collection of trigger events and the estimated likelihood. Now they can all be brought together in the top-level risk analysis document.

It should be noted that a preferred method for combining the severity of an injury and the likelihood that it will occur is a tabular or graphic method. Using this method, a table is created with one axis labeled with descriptions of different levels of likelihood and the other with descriptions of the various levels of severity (see Table I). Avoiding numeric values helps avoid the traps associated with the use of numbers and calculations (risk priority number or RPN method). However, for the purpose of this article and in order to quickly and clearly demonstrate the concepts being discussed, the RPN method is used.

Using the numeric approach, each identified trigger event should be associated with the likelihood that it will occur. Likelihood is represented using a ranking of (for example) 1 through 5, with 1 being highly unlikely to occur and 5 being a relative certainty. Caution is advised when assigning likelihood rankings. Many individuals (especially those with strong mathematics backgrounds) spend extended periods of time attempting to accurately assign probabilities or to differentiate which ranking a given trigger event should be assigned. Generally such discussions are not productive considering that each ranking represents an extremely broad range of actual probabilities and, in the end, the ranking given is at best an estimate.

 It is important to keep in mind that ISO 14971 requires that the level for each risk be estimated twice. The standard requires estimating the risk both before risk-reduction techniques (frequently called mitigations) have been implemented and then again after risk-reduction techniques have been put in place. It is common during the initial (premitigation) estimation of risk that extended disagreements over likelihood rankings occur. As mentioned earlier, if these discussions are focused on the accuracy of the likelihood, resources are almost certainly being wasted.

In addition, design engineers often argue that the likelihood that a harm will occur is extremely small “because it will comply with the appropriate standards.” However, compliance with standards is a risk-reduction technique and is therefore not applicable for premitigation risk. Typically, engineers are trained to associate problems with solutions. But protracted discussions about likelihood are almost always a waste of time during initial risk estimation.

Designers are not the only members of the risk analysis team that can be misled in the likelihood estimation process by their background and training. Commonly, quality engineers and regulatory personnel attempt to use resources such as the FDA medical device reports (MDR) database or the European Union vigilance database to estimate premitigation likelihood. These databases can certainly provide useful information in identifying trigger events and harms, but they have no value in estimating the likelihood that an injury will occur without a risk-reduction technique being employed. Presumably, at least, all devices on the market have had risk mitigations implemented or they would not have been allowed on the market by regulators. As a rule, the information available from such resources is a better indication of the acceptable level of risk for devices that have had all risks reduced. In other words, the devices in these databases represent broadly acceptable levels of risk assuming that the injuries that have occurred did not result in recalls, other regulatory action, or extensive lawsuits.

What makes more sense in terms of efficiency is to remember that without any risk-mitigation technique employed (initial risk level), the likelihood of injury is extremely high or at least inestimable. ISO 14971 says that when we cannot estimate likelihood, we should default to the highest level of likelihood. Will this result in an unacceptable risk? Of course. But that's OK because we haven't tried to reduce it to acceptable levels yet. What we have accomplished, though, is reducing or eliminating long, drawn out, and completely unproductive arguments. For most risks, simply identify the appropriate requirement from a consensus safety standard as the mitigation. That will make the risks acceptable (see Annex D item D.5.5 of the standard).

 After the trigger events associated with each hazard have been identified and the likelihood of an event is estimated, the harms that would occur and their severity must be identified. As a rule, this phase of the process goes fairly smoothly with minimal disagreement. Generally the team can quickly agree on how badly an individual would be harmed based on the hazard.

 Risk Quantification

Once the trigger event has been identified and its likelihood and the severity of the resulting harm estimated, the risk can be quantified. This can be done through any number of techniques, but this example will simply multiply the likelihood and severity.

However, it is important to remember that the resulting risk ranking has little or no meaning outside the analysis in which it is used. Although determinations from previous risk analyses for similar devices can be used as an input or guide, it cannot be directly transferred from device to device or from analysis to analysis. The only value a risk ranking provides is as a tracking method to determine the relative level of risk before and after mitigation techniques are identified and applied, and whether the value has been reduced to an acceptable level.

Risk Evaluation

The steps described so far complete the initial or premitigation risk estimation phase. The risk values derived for each harm must now be considered to determine whether it is higher than the acceptability threshold for the device. For those cases in which the risk level exceeds the threshold, risk-reduction techniques must be implemented to reduce those risks to acceptable levels.

 In determining a policy for the acceptability of risk, many manufacturers have implemented a concept from an informative annex of the standard. The annex was intended only to demonstrate how society perceives risk: the three-region risk chart, which includes acceptable risks, unacceptable ones, and risks that are as low as reasonably practicable (ALARP). This chart was provided in the original edition of ISO 14971 to show that there are some risks that everyone would consider unacceptable, some that would be thought of as acceptable by the general public, and, of course, some on which reasonable individuals might disagree. It was never meant to be a model for determining the acceptability of risks. ALARP is intended to be used in risk management only as a policy requiring that some risks that qualify as acceptable (but that are close to the acceptability threshold) should be further reduced if possible.

The standard requires that risks be identified only as acceptable or unacceptable. Introduction of a third undefined level of acceptability adds confusion but no value. In most cases in which the

concept of ALARP has been misapplied, it is used to label this middle region. Processes using this method typically say that risks in the ALARP zone require a risk-benefit analysis. They also say that risks below this zone are broadly acceptable and require no risk reduction, and that risks above ALARP are unacceptable. The problem with this approach is that it eliminates risk-benefit analysis as a tool for many risks such as those associated with high-risk but high-reward procedures (e.g., open-heart surgery). However, if a simple two-region risk acceptability model is used, risks are either acceptable and need not be reduced further, or they are unacceptable and action must be taken to either reduce the likelihood of the trigger event (most common) or the severity of the harm. Risk-benefit analysis then becomes what it was intended to be by ISO 14971: a way to show that otherwise unacceptable risks are acceptable only because significant benefit is provided that could not exist without that risk.

It should also be noted that when risks are near but still below the acceptable risk threshold, ISO 14971 says that we should evaluate whether additional risk mitigations can be employed.

This concept is intuitively obvious. As discussed, all risk estimations are just that—estimations that inherently carry the potential for error. When those errors might result in a risk that is acceptable but near the acceptability threshold, additional reduction in that risk is advised to ensure an adequate margin. A historic evaluation (as required by subclause 3.2 of the risk management standard) can provide insight on the accuracy of your risk management process and help in determining when additional mitigations are appropriate for otherwise acceptable risks.

Risk Reduction

For those risks that are unacceptable based on the manufacturer's policy or method for evaluating risk, risk-reduction techniques must be implemented to reduce the level of risk to acceptable levels. Those techniques include design features to reduce the likelihood of the trigger event or the severity of the harm that would result. Where design solutions are not practicable, manufacturers might implement guards that prevent access to the harm. When neither design solutions nor guards are practicable, warnings may be provided through labeling or instructions. Remember that warnings are an acceptable solution for reducing risk only when design solutions or guards (which could be considered a design solution) are not reasonably practical. Resorting to warnings without documenting why design or guard solutions are not reasonable may lead to objections by regulators and auditors. Moreover, in court, the manufacturer may be characterized as having resorted to a perceived cheap solution rather than taking appropriate action to protect patients, clinicians, and bystanders.

However, if the manufacturer has effectively used device safety standards, it won't need to start a desperate search for practical risk-reduction techniques. The standards used to identify hazards associated with the device provide risk-reduction techniques for each of those hazards. Furthermore, ISO 14971 says that when manufacturers comply with the requirements of those safety standards, the hazards (and risks) associated with each requirement are presumed to be broadly acceptable and no further mitigation is required. This means that for each hazard and associated risk derived from standards, compliance with the requirement is identified as risk mitigation and sets the postmitigation risk level well within the company's acceptable risk range.

Note that this approach has not estimated the postmitigation likelihood in these cases; it is not necessary. The severity of the harm (determined in the premitigation analyses) and the resulting risk level (broadly acceptable) are known. Therefore, the likelihood that would drive the level of risk can be calculated. When standards are used properly, hazards, harms, and mitigations are identified. This eliminates the need to make likelihood estimates either pre- or postmitigation. For most medical devices (depending on the number of standards available for the device), well over 90% of the hazards and the levels of risk can be identified and reduced to acceptable levels thoroughly, and with minimum time expenditure.

The techniques outlined here won't eliminate the need to think “outside of the standard” and identify hazards and risks that are unique to a device being evaluated. New features and creative solutions to common problems always have the potential to give rise to unique risks that must also be made acceptable.

Conclusion

ISO 14971 requires that manufacturers identify any new hazards and risks that might have been created by risk-reduction techniques. For virtually all of the risk reductions derived from standards, there will be no additional risks created (or they would be addressed by other requirements in those standards). However, when manufacturers develop their own unique risk mitigations, this type of analysis is critical.

In the end, thoroughly understanding the risk management process and its purpose as well as implementing standards as an integral part of that process, can significantly improve both the effectiveness and efficiency of a device company's risk management efforts.

2. Explain briefly with examples, six maintenance scheduling principles.

Sol:Follow these planning, scheduling principles

In the first two issues of Reliable Plant, I outlined why planning frustrates many companies and why many planners do not plan. I explained that serious frustration stems from incorrectly encouraging supervisors to wait on planning for all reactive work. I also wrote that planners commonly help jobs in progress to the extent that they have no time left to plan new work.

With these major issues addressed, this column enumerates all of the principles of a successful planning and scheduling program. The six planning principles and six scheduling principles listed on this page form the essence of my “Maintenance Planning and Scheduling Handbook”.

Planning Principle 1 requires keeping planners independent from the supervision of the individual crews. Supervisors commonly grab planners to help on jobs, making them unavailable for planning.

Planning Principle 2 is to have the planners (now available for planning) concentrate on planning future work rather than merely helping deal with delays of jobs already in progress. This principle takes advantage of the repetitious nature of most maintenance work and moves jobs up a learning curve.

Planning Principle 3 recognizes that planners can only practically retrieve prior job feedback to improve jobs if the file or computer system tracks jobs at the component level (e.g., a valve instead of a system).

Planning Principle 4 utilizes the expertise of an experienced technician as a planner (with perhaps limited history review) to estimate job labor hours. This avoids time-consuming techniques of building estimates.

Planning Principle 5 has this planner utilize the skills of the field technicians and avoid extra time giving more procedural information than necessary on initial job plans.

Planning Principle 6 reminds us that the purpose of planning is to reduce delays and help technicians spend more time on jobs.

Planning also involves scheduling because reducing delays during individual jobs allows supervisors to assign more jobs. Scheduling answers the question of how many jobs to assign. While the planning principles address major issues, the scheduling principles are more of a framework.

Scheduling Principle 1 obligates each job plan to estimate labor hours and craft skill levels.

Scheduling Principle 2 encourages not interrupting jobs already in progress through proper prioritization of work.

Scheduling Principle 3 commits crew leaders to forecast labor hours for craft skills available for the next week.

Scheduling Principle 4 combines all of the forecast crew labor hours with the estimated labor hours of the planned jobs, generally in order of job priority.

Scheduling Principle 5 has crew leaders schedule and assign daily work (even though the planning department allocates the week’s goal of work).

Scheduling Principle 6 establishes the importance of measuring schedule success. Measuring this outcome helps management insure that planning and scheduling does take place.

Finally, maintenance must acknowledge reactive work. Management must assure crew leaders that for urgent work, it is OK to work an unplanned job and it is OK to break a schedule. Planning must not constrain crews from immediately beginning work on urgent jobs. Nevertheless, planning can abbreviate its efforts on urgent work and many times produce a helpful job plan before maintenance begins work.

Allowing crews to work unplanned work and break schedules is vital to consider, especially for reactive plants. If it is OK to work on unplanned jobs and break schedules, where is the productivity gain? Actual experience shows that simply starting each crew every week with a sufficient allocation of work as a goal significantly boosts crew productivity, usually in excess of 50 percent.

This column and my previous two are most appropriate for readers that already recognize the value of a planning program. My column in the January/February issue will address and quantify the value of maintenance planning. Future articles after that will review the principles in greater depth and will also handle individual issues that commonly arise in planning efforts.

3. Write a note on: a) Productive Maintenance. b) Predictive Maintenance. c) Condition Based Maintenance.

Sol:a) Total Productive Maintenance

One of the most recognizable symbols in modern manufacturing is the “TPS House” diagram as shown below. The diagram is a simple representation of the Toyota Production System (TPS) that Toyota developed to teach their supply base the principles of the TPS. The foundation of the house represents operational stability and has several components, one of which is Total Productive Maintenance.

    

Working with little inventory and stopping production when there is a problem causes instability and a sense of urgency among workers. In mass production, when a machine goes down, there is no sense of urgency; excess inventory will keep the operation running while maintenance fixes the problem. In lean production, when an operator shuts down production to fix a problem, the line will soon stop producing, creating a crisis and a sense of urgency. A properly implemented and maintained Total Productive Maintenance System (TPM) will provide the needed stability for lean production.

A little more than 30 years ago, an automotive supplier company in Japan (Nippondenso) realized that until you address and systematically eliminate the causes of poor equipment performance, you cannot deliver to your customers “just in time,” improve quality levels, lower operating costs or improve profits. In 1969, the ideas of Total Productive Maintenance, facilitated by Seiichi Nakajima, helped take the Toyota Production System to the next level.

Since the Toyota Production System was focused on the absolute elimination of waste to reduce manufacturing cost, TPM was designed to systematically identify and eliminate equipment losses (downtime, inefficiency, defects). In implementing lean manufacturing practices, machine availability plays an important role. Preventive maintenance is a key aspect in ensuring machine availability. This practice achieves maximum efficient usage of machines through total employee involvement.

Toyota has created an organizational culture that encourages employee participation, which is essential for successful TPM. Group activities are promoted among the shop-floor team members. The knowledge base of all the employees is used to improve equipment reliability and productivity thereby lowering maintenance and operating costs. Two other important aspects of TPM are training and open communication between operators and engineering. Production personnel are trained to perform routine maintenance.

The traditional approach to preventive maintenance is a clear-cut division of labor.

Machine operators perform routine maintenance functions. Maintenance technicians are responsible for specialized maintenance and for improving maintainability.

Engineering is responsible for improving the process.

This practice is not capable of achieving the TPM targets, as there is a lack of communication between operating and maintenance teams.

Nippondenso came out with an alternative approach of appointing a machine technician (MT) that supports communication between operators and maintenance. The responsibilities of the MT were to perform minor maintenance and repair tasks. These MTs underwent classroom training on tool finishing and fitting as well as on-the-job training. On-the-job training gave them exposure to machines and helped them gain expertise in their area.

There are two different types of philosophies of TPM. Firstly, there is the centralized maintenance approach. This requires maintenance personnel to be cross-trained, thus providing flexibility of using a number of workers for scheduling maintenance tasks. This flexibility is essential because as workers move up in seniority level, there is a tendency to opt for convenient shifts instead of third shift.

The second approach is decentralization. As personnel become more experienced in one functional area, they gain more expertise. Sometimes it requires six months of training before a person becomes proficient in a new area. Thus, frequent job rotations may result in under-utilization of skills gained through training. A good example of this type of approach is at Honda Motors for its three departments – suspension assembly, facilities and engine assembly. Each department has a separate maintenance team. The reasons for this shift were the need for 12 to 18 months of training in each area, and local regulations required maintenance to take place only on weekends and shutdowns.

Toyota has a centralized maintenance function with cross-trained employees. The benefits of decentralized maintenance are derived from the use of MTs. These MT’s are experts in their

areas. However, availability of limited maintenance personnel necessitates cross-trained employees.

Toyota also collects data for analysis and trend establishment. Sufficient data on the trend and pattern of equipment’s performance should be available for identifying and setting up standards and procedures for preventive maintenance. This data would also be useful in determining costs of preventive maintenance and repairs, run-to-failure vs. preventive maintenance, and failure history.

Organizations also need to evaluate the impact of organizational structure and processes on preventive maintenance. Change in these can have an overwhelming impact on employee morale, efficiency and effectiveness. As Toyota has shown, preventive maintenance management calls for long-term commitment to the goal and pays dividends in the long run.

b) Predictive MaintenancePredictive maintenance (PdM) techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. This approach offers cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted.

Predictive Maintenance or condition-based maintenance, attempts to evaluate the condition of equipment by performing periodic or continuous (online) equipment condition monitoring. The ultimate goal of Predictive Maintenance is to perform maintenance at a scheduled point in time when the maintenance activity is most cost-effective and before the equipment loses performance within a threshold. This is in contrast to time- and/or operation count-based maintenance, where a piece of equipment gets maintained whether it needs it or not. Time-based maintenance is labor intensive, ineffective in identifying problems that develop between scheduled inspections, and is not cost-effective.

The "predictive" component of predictive maintenance stems from the goal of predicting the future trend of the equipment's condition. This approach uses principles of statistical process control to determine at what point in the future maintenance activities will be appropriate.

Most PdM inspections are performed while equipment is in service, thereby minimizing disruption of normal system operations. Adoption of PdM can result in substantial cost savings and higher system reliability.

Reliability-centered maintenance, or RCM, emphasizes the use of predictive maintenance (PdM) techniques in addition to traditional preventive measures. When properly implemented, RCM provides companies with a tool for achieving lowest asset Net Present Costs (NPC) for a given level of performance and risk.

Technologies

To evaluate equipment condition, predictive maintenance utilizes nondestructive testing technologies such as infrared, acoustic (partial discharge and airborne ultrasonic), corona

detection, vibration analysis, sound level measurements, oil analysis, and other specific online tests. New methods in this area are to utilize measurements on the actual equipment in combination with measurement of process performance, measured by other devices, to trigger maintenance conditions. This is primarily available in Collaborative Process Automation Systems (CPAS). Site measurements are often supported by wireless sensor networks to reduce the wiring cost.

Vibration analysis is most productive on high-speed rotating equipment and can be the most expensive component of a PdM program to get up and running. Vibration analysis, when properly done, allows the user to evaluate the condition of equipment and avoid failures. The latest generation of vibration analyzers comprises more capabilities and automated functions than its predecessors. Many units display the full vibration spectrum of three axes simultaneously, providing a snapshot of what is going on with a particular machine. But despite such capabilities, not even the most sophisticated equipment successfully predicts developing problems unless the operator understands and applies the basics of vibration analysis.

Acoustical analysis can be done on a sonic or ultrasonic level. New ultrasonic techniques for condition monitoring make it possible to “hear” friction and stress in rotating machinery, which can predict deterioration earlier than conventional techniques. Ultrasonic technology is sensitive to high-frequency sounds that are inaudible to the human ear and distinguishes them from lower-frequency sounds and mechanical vibration. Machine friction and stress waves produce distinctive sounds in the upper ultrasonic range. Changes in these friction and stress waves can suggest deteriorating conditions much earlier than technologies such as vibration or oil analysis. With proper ultrasonic measurement and analysis, it’s possible to differentiate normal wear from abnormal wear, physical damage, imbalance conditions, and lubrication problems based on a direct relationship between asset and operating conditions.

Sonic monitoring equipment is less expensive, but it also has fewer uses than ultrasonic technologies. Sonic technology is useful only on mechanical equipment, while ultrasonic equipment can detect electrical problems and is more flexible and reliable in detecting mechanical problems.

Infrared monitoring and analysis has the widest range of application (from high- to low-speed equipment), and it can be effective for spotting both mechanical and electrical failures; some consider it to currently be the most cost-effective technology.

Oil analysis is a long-term program that, where relevant, can eventually be more predictive than any of the other technologies. It can take years for a plant's oil program to reach this level of sophistication and effectiveness. Analytical techniques performed on oil samples can be classified in two categories: used oil analysis and wear particle analysis. Used oil analysis determines the condition of the lubricant itself, determines the quality of the lubricant, and checks its suitability for continued use. Wear particle analysis determines the mechanical condition of machine components that are lubricated. Through wear particle analysis, you can identify the composition of the solid material present and evaluate particle type, size, concentration, distribution, and morphology.

c) Condition Based Maintenance:

Condition-based maintenance (CBM), shortly described, is maintenance when need arises. This maintenance is performed after one or more indicators show that equipment is going to fail or that equipment performance is deteriorating.

Condition-based maintenance was introduced to try to maintain the correct equipment at the right time. CBM is based on using real-time data to prioritize and optimize maintenance resources. Observing the state of the system is known as condition monitoring. Such a system will determine the equipment's health, and act only when maintenance is actually necessary. Developments in recent years have allowed extensive instrumentation of equipment, and together with better tools for analyzing condition data, the maintenance personnel of today are more than ever able to decide what is the right time to perform maintenance on some piece of equipment. Ideally condition-based maintenance will allow the maintenance personnel to do only the right things, minimizing spare parts cost, system downtime and time spent on maintenance.

Challenges:

Despite its usefulness, there are several challenges to the use of CBM. First and most important of all, the initial cost of CBM is high. It requires improved instrumentation of the equipment. Often the cost of sufficient instruments can be quite large, especially on equipment that is already installed. Therefore, it is important for the installer to decide the importance of the investment before adding CBM to all equipment. A result of this cost is that the first generation of CBM in the oil and gas industry has only focused on vibration in heavy rotating equipment.

Secondly, introducing CBM will invoke a major change in how maintenance is performed, and potentially to the whole maintenance organization in a company. Organizational changes are in general difficult.

Also, the technical side of it is not always as simple. Even if some types of equipment can easily be observed by measuring simple values as vibration (displacement or acceleration), temperature or pressure, it is not trivial to turn this measured data into actionable knowledge about health of the equipment.

Value potential

As systems get more costly, and instrumentation and information systems tend to become cheaper and more reliable, CBM becomes an important tool for running a plant or factory in an optimal manner. More optimal operations will lead to lower production cost and lower use of

resources. And lower use of resources may be one of the most important differentiators in a future where environmental issues become more important by the day.

A more down to earth scenario where value can be created is by monitoring the health of your car motor. Rather than changing parts at predefined intervals, the car itself can tell you when something needs to be changed based on cheap and simple instrumentation.

It is Department of Defense policy that condition-based maintenance (CBM) be "implemented to improve maintenance agility and responsiveness, increase operational availability, and reduce life cycle total ownership costs".

Assignment Set – 2

1. Explain Master Production Schedule. Take any product around you and prepare a detailed Bill of materials for the same.

Sol:Master production scheduleIntroduction: The master production schedule (also commonly referred to as the MPS) is effectively the plan that the company has developed for production, staffing, inventory, etc.

It has as input a variety of data, e.g. forecast demand, production costs, inventory costs, etc and as output a production plan detailing amounts to be produced, staffing levels, etc for each of a number of time periods.

This production plan: operates at an aggregate level (that is it does not usually go into great detail about parts to be used, etc - hence the name aggregate planning); and is cost driven, that is it attempts to meet the specified requirements at minimum cost. The idea of a master production schedule can best be illustrated by means of an example.

Example: In our example we have just a single product being produced. Production takes place each period (week) either in the normal (regular) production shift or in overtime associated with that shift. There is only one shift (i.e. not operating a two/three shift system - such as with "round-the-clock" working).

Completed items can also be "bought-in" from a subcontractor (at a cost).

We are allowed to hire/fire workers (again at a cost). Backorders are also allowed (recall here that backorders are customer orders that cannot be satisfied in the required period, but the customer allows the order to remain open to be fulfilled in a later period). Lost sales are not allowed.

The diagram below illustrates the situation and the types of factor with which we are dealing graphically.

The data for the example we consider is as below, where we have shown the initial data entry screen from the package.

In the above screen we have chosen the "General LP Model". This is the most general of the options allowed by the package. LP stands for linear programming and is a generalized way of modeling decision problems. To ease data entry we have not crossed the "Part Time Allowed" box - if we had then we would have had the option of dealing with part time employees.

We have also not crossed the "Lost Sales Allowed" box - if we had then we would have allowed lost sales. In general a company may allow lost sales because the company finds that customers simply do not backorder - i.e. a lost sale is automatic if the product is not immediately available; or the company is prepared to allow lost sales as it may be better to allow orders to be lost than to allow such orders to become backorders (thereby incurring backorder costs).

The remaining boxes have been crossed and so we can deal with: overtime hiring/firing subcontracting backorders

In our example above we have just 4 periods (weeks) - this is our time horizon (planning period). We are dealing with employees working hours in each week. Two employee hours are required to produce one unit of each product and the initial number of employees is 10. At the start of the planning period there is no initial inventory (nor are there any backorders).

The data for our example entered into the package in the light of the choices made at the initial screen is as below:

The meaning of each of these lines of data is given below:

Forecast Demand - this is the forecast demand for the product in each of our 4 periods (weeks).

Initial Number of Employee - this is the initial number of employees in each week, here just the 10 employees we have currently.

Regular Time Capacity in Hour per Employee - this is how many regular hours each employee works per week, here 35 hours

Regular Time Cost per Hour - this is the cost per hour of regular time worked, here £15

Under time Cost per Hour - this is the cost per hour of not using a worker to their full regular capacity, here zero

Overtime Capacity in Hour per Employee - this is the maximum number of hours each employee can work in overtime per week, here 10 hours

Overtime Cost per Hour - this is the cost per hour of overtime, here £25

Hiring Cost per Employee - this is the cost of hiring one employee, here £500

Dismissal Cost per Employee - this is the cost of dismissing (firing) one employee, here £2000

Maximum/Minimum Number of Employee Allowed - here we can set limits on the maximum and minimum number of employees, here M signifies there is no limit on the maximum number and the minimum number is 8. In general there may be an upper limit on the number of employees due to physical capacity constraints.

Initial Inventory (+) or Backorder (-) - the initial inventory available or backorders outstanding, here zero

Maximum/Minimum Ending Inventory - here we can set limits on the maximum and minimum number of product units in stock at the end of each week, here M signifies there is no limit on the maximum number and the minimum number is zero. In general there may be an upper limit because we have a limited space in which to store stock. The minimum number corresponds to safety stock that may be kept in case of unforeseen demand.

Unit Inventory Holding Cost - this is the cost of holding one unit in stock at the end of each period, here £3

Maximum Subcontracting Allowed - this is the maximum number of product units we are allowed to buy in from the external subcontractor, here there is no limit on the amount that may be bought in. In general there may be a limit on the total amount the subcontractor can supply to us each period.

Unit Subcontracting Cost - this is the cost of each unit bought from the external subcontractor, here £60

Maximum Backorder Allowed - this is the maximum number of backorders allowed at the end of each period, here there is no limit on the number of backorders that can be held at the end of each period.

Unit Backorder Cost - this is the cost of each backorder outstanding at the end of each period, here the M signifies that each backorder is very expensive. The effect of M here will be to ensure that (if at all possible) backorders will be avoided.

Other Unit Production Cost - this is the cost of producing one unit of the product that is not already accounted for by employee costs - here zero

Capacity Requirement in Hour per Unit - this is the number of employee hours that are required to produce one unit of the product, here 2 hours

In order to ease understanding of the problem most of the above data items take the same value in each and every period (week). However it would be perfectly possible for them to have different values in each week.

Consider for a moment this example as we have defined it so far. We have a single product, are planning over 4 time periods, have regular time and overtime, can buy from an external subcontractor, and are allowed to hire and fire employees. Some of the decisions we must make are shown below: Period 1 2 3 4 Amount to produce using regular time ? ? ? ? Amount to produce using overtime ? ? ? ? Amount to purchase from subcontractor ? ? ? ? Number of backorders ? ? ? ? Number to hire ? ? ? ? Number to fire ? ? ? ?

You can see from this matrix that there are already 24 decisions which we have to make. For such problems decision models (such as the decision model used within the package) are much better at decision-making than people. Moreover such models can guarantee to make decisions at minimum cost, something people cannot do.

Note here that even the (cheap) package used here is extremely flexible in terms of the situations it can consider.

SolutionThe solution to the problem is shown below:

It can be seen that we immediately hire more employees, and that these are employed throughout the planning period of 4 weeks. Note that the number hired is 10.57 - i.e. it includes a fraction of an employee. This often happens in aggregate planning and can usually be ignored (simply round to the nearest appropriate whole number). Reflect that we are producing a plan for production over a 4 week period. It is unlikely that our demand forecasts will be completely accurate and hence this rounding need not concern us unduly.

With 10+10.57 = 20.57 employees working 35 hours a week we have a regular time capacity of 20.57x35 = 720 employee hours (approximately) and at 2 hours per unit produced this corresponds to a regular time production of 360 units - precisely as above, i.e. over the 4 week planning period we are planning to work all of our employees to their full regular time capacity. As can be seen above we are planning no overtime or subcontracting.

Note the build into inventory that occurs in various periods. As inventory costs us money let us be clear about why the above (the minimum cost solution) involves build into inventory. It is to meet future demand. Demand for the product increases over the 4 week planning period (from 250 to 450 units) and the package has determined that the most cost-effective way to ensure that this demand is met is to build into inventory in earlier periods. Note that an alternative strategy to meet this increased demand would be to buy from the subcontractor, were this cheaper the package would have adopted that strategy.

The costs associated with the package solution can be seen below:

The production and employment strategy given above is the minimum cost strategy since the package uses linear programming to calculate a schedule for production and staffing that meets the forecast demand and also satisfies the other constraints that we place upon the problem at minimum cost. It would be impossible to find the minimum cost solution manually - consider the solution shown with an increase in employment and with varying amounts built into inventory - could that ever be produced by a person in the time (fraction of a second) it takes the package to produce it?

Level and chase strategiesWe may be interested in a solution that consists of a fixed number of workers (a level strategy). This can be seen below where we have fixed the maximum and minimum number of employees to 10 (the current number) in each and every period.

The solution for this level strategy is shown below.

It can be seen that with this solution we use both overtime and subcontracting but do not build into inventory. The total cost of 63,400 is much more than the previous (non-level) strategy which had a total cost of 49475.71If we change the hire/fire costs to zero and reset the limits on the maximum/minimum number of employees then we will produce a chase strategy (ramp workforce up/down as required). This solution can be seen below.

BackorderingIn our original situation considered above, with costs for hiring and firing, we were prohibiting backorders by making them very expensive. Suppose now that backorders cost us £1 per period (week). The effect of this on the solution is shown below.

It can be seen that we produce nothing - the cheapest solution is simply to allow backorders to build up over the planning period. This seems silly and for this reason it is usual to insist that there are no backorders outstanding at the end of the planning period. This is an assumption that is, by convention, applied and is a reasonable assumption when planning over a relatively long time period. Moreover unless this is assumed it can happen that the best thing for the company to do over the planning period is simply to allow backorders to build up (as above).To ensure that there are no backorders outstanding at the end of the planning period we enter a zero for "Maximum Backorders Allowed" in the last period (week 4), as below.

The solution is

which is effectively the same as the initial solution we considered. However to illustrate that backorders can play a role suppose that we: have a level strategy with exactly 10 employees in each and every period (week); and restrict the subcontractor capacity in each and every periodthen the input is as below:

and the output is:

where backorders do occur since production capacity (both regular time and overtime) together with subcontractor capacity is insufficient to met demand in some periods.

2. Describe Close Work in Work Management Process. Explain components of work execution.

Sol:The purpose of this article is to provide you with everything you need to know about Work Breakdown Structures (WBS) so you can improve the way you plan, manage, and control your projects and programs.

PMBOK defines a WBS as “a deliverable-oriented hierarchical decomposition of the work to be executed by the project team, to accomplish the project objectives and create the required deliverables. The WBS defines the total scope of the project.”

An easier way to think of Work Breakdown Structures is as being similar to a family tree, that is, they are a tree structure showing the subdivision of components necessary to deliver a project or program. Work Breakdown Structures are very useful for establishing agreement between stakeholders and project team members as to the scope of the project.

In a general sense, we can think of WBS as follows:

If we think about starting a project, we begin with a project charter and preliminary scope statement. This defines the high-level goals and deliverables of the project. We then create the project scope document which further defines these deliverables into a list of all deliverables and the requirements of each. The next step is to use this comprehensive list of deliverables to build the WBS.

The WBS will detail the full scope of the work necessary to finish the project. The WBS can then be used to estimate the cost of the project, schedule resources, and plan quality gates. Essentially the WBS will enable you to better manage your project.

Some WBS ExamplesThe best way to understand work breakdown structures is by means of some examples. We’ll look at two examples, one which looks at the components that make up a Car, and another which looks the components that make up a Project. Firstly, lets look at the components which make up a car.

At the very top of the WBS is the project or program name, in this case Car. The lowest level of any WBS is always called the work package level. Thus, in the example above, 4.0 Chassis is a work package to deliver the Chassis in it’s entirety for the car.

Now let’s consider the WBS for the Project:

 Here we can see that the project is made up of four phases: Requirements, Design, Build, and Deliver.

One way to think about these two examples is that the Car example is showing the “what” (the components of the car), and the Project example is showing the “how” (the components needed to deliver a generic project).

Getting to a Point Where we can start to planWe do this using the process of decomposition. Decomposition is a 5-step process:

1. Identify all the major project deliverables. One way to do this is to involve the project team as a group to identify all the major deliverables from the project scope statement.2. Organize the WBS (we’ll cover next)3. Define the WBS components. Here we decompose the major deliverables defined in step 1 into lower level components.4. Assign identification codes. This can be done simply by attaching a number to each of the WBS components. All the examples I’ve used have identification codes attached.5. Verify the WBS. Here we validate the WBS for correctness. Ask yourself and the team questions such as “are all the components clear?” Are all components complete? Is each component absolutely necessary? Does the decomposition sufficiently describe the work which needs to be done?

It’s a lot of work to do this, but really beneficial if you’re at the early stages of managing your project or program. By deconstructing the tasks you may identify areas you would not have otherwise noticed until later in the project execution. This makes you more likely to get

things right up front and stops the teams getting frustrated because you will not be asking them to change things several times during the project.

Organizing the WBSPMBOK states that you can organize the WBS in several ways:

Major Deliverables and subprojects: here the major deliverables of the project or program are used as the first level of decomposition. This is the approach we used for the Car example above. Subprojects executed outside the project team: you can think of this as being a little like streams within a program. For example, if on one stream is to rollout the product globally, then the rollout project manager can define the WBS for this component. Often a subproject will be contracted out. Project phases: using this technique, each phase of the project would be listed in the first level of decomposition, with the deliverables of each phase listed in the next level. This is the approach we used for the Project example previously. Combination approach: this is a combination of the organizational methods, for example, you might have subprojects listed on the first level, with the major deliverables of each listed on the 2nd level.

When to StopDon’t go crazy when creating your Work Breakdown Structures. What you’re trying to do is define the work of the project or program so you can easily plan, manage and control that work. You should only decompose the plan to a level that allows you to achieve this aim.

WBS and AgileHaving read this far, you may well be thinking that work breakdown structures are very old fashioned and don’t apply to Agile. However, WBS equally applies to Agile. An agile WBS is organized around end-user functionality. Here, features are decomposed into Epics, Epics into User Stories, and User Stories are decomposed into Functionality which can be implemented within a single iteration. Because an individual user story is atomic, stories can be added or removed from the WBS provided the sum of the work can still be implemented within one sprint.

At this point I think I should add a personal note on this. This is theory of Agile work breakdown structures, but I don’t in practice think it is necessary to do this, as most Agile methods effectively make this a duplication of effort.Unique WBS IdentifiersIt’s good practice to assign a unique identifier to each level of the WBS. For example, we might use the following based on the Car example we looked at earlier:

Work PackagesAs mentioned previously, the lowest level in a WBS is a work package. Work packages are components which can easily be given to a person, a team, or a subcontractor, who then has accountability and responsibility for delivering the work package.

In programs or large projects a work package may be at a level requiring further decomposition into its own work breakdown structure. The breakdown of the work package might then be done by the project team for that work package or even an external vendor.Scope BaselineNow that you have created the Work Breakdown Structure you are ready to baseline the scope of the project or program you are managing. The scope baseline for your project or program is defined as the approved project scope statement, the work breakdown structure, and the WBS dictionary.Design Principles when Constructing Work Breakdown StructuresWhen constructing work breakdown structures there are a couple of guiding principles you need to know to keep you on track: The 100% Rule: The WBS should define the total scope of the project. If it doesn’t do this then the plans you create from the WBS will by inference have gaps and missing components. Mutual Exclusivity:  there should be no overlap between any two elements in a WBS. If there are, then you run the risk of duplicating work in the project execution Include Deliverables, Not Actions: I’m not going to go into details (you’ve done well to read this far already) but this is one of the best ways to stick to the 100% rule Use Common Sense: as mentioned previously, don’t go into too much detail. What you’re looking for is enough detail so you can plan, manage and control the project.

3. Explain in detail by taking an example the difference between Preventive and Breakdown Maintenance. Which of them is preferred? Justify your choice.

Sol:Preventive maintenance (PM) has the following meanings:1. The care and servicing by personnel for the purpose of maintaining equipment and facilities in satisfactory operating condition by providing for systematic inspection, detection, and correction of incipient failures either before they occur or before they develop into major defects.2. Maintenance , including tests, measurements, adjustments, and parts replacement, performed specifically to prevent faults from occurring.Preventive maintenance can be described as maintenance of equipment or systems before fault occurs. It can be divided into two subgroups: planned maintenance And condition-based maintenance.

The main difference of subgroups is determination of maintenance time, or determination of moment when maintenance should be performed.

While preventive maintenance is generally considered to be worthwhile, there are risks such as equipment failure or human error involved when performing preventive maintenance, just as in any maintenance operation. Preventive maintenance as scheduled overhaul or scheduled replacement provides two of the three proactive failure management policies available to the maintenance engineer. Common methods of determining what Preventive (or other) failure management policies should be applied are; OEM recommendations, requirements of codes and legislation within a jurisdiction, what an "expert" thinks ought to be done, or the maintenance that's already done to similar equipment, and most important measured values and performance indications.

To make it simple: Preventive maintenance is conducted to keep equipment working and/or extend the life of the equipment. Corrective maintenance, sometimes called "repair", is conducted to get equipment working again.

The primary goal of maintenance is to avoid or mitigate the consequences of failure of equipment. This may be by preventing the failure before it actually occurs which Planned Maintenance and Condition Based Maintenance help to achieve. It is designed to preserve and restore equipment reliability by replacing worn components before they actually fail. Preventive maintenance activities include partial or complete overhauls at specified periods, oil changes, lubrication and so on. In addition, workers can record equipment deterioration so they know to replace or repair worn parts before they cause system failure. The ideal preventive maintenance program would prevent all equipment failure before it occurs.

There is a controversy of sorts regarding the propriety of the usage “preventative.” The consensus of internet entries concerning the respective usages seems to indicate that “preventive” is the preferred term.

Breakdown Maintenance - Breakdown maintenance implies that repairs are made after the equipment is out of order and it cannot perform its normal function any longer, e.g., an electric motor of a machine tool will not start, a belt is broken, etc.

Under such conditions, production department calls on the maintenance department to rectify the defect. The maintenance department checks into the fault and makes the necessary repairs. After removing the fault, maintenance engineers do not attend the equipment again until another failure or breakdown occurs. This type of maintenance may be quite justified in small factories which:

1. are indifferent to the benefits of scheduling;2. Do not feel a financial justification for scheduling techniques; and3. Get seldom (temporary or permanent) demand in excess of normal operating capacity. In many factories make-and-mend is the rule rather than the exception.

Breakdown maintenance practice is economical for those (non-critical) equipments whose downtime and repair costs are less this way than with any other type of maintenance. Breakdown type of maintenance involves little administrative work, few records and a comparative small staff. There is no planned interference with production programmes.