In today’s dynamic environment, a reliable production system is considered as a critical factor for competitiveness; thus, maintenance has risen from a mere tactical to a more strategic level for manufacturing organisations (Brah & Chong, 2004; Pinjala, Pintelon, & Vereecke, 2006).
Total productive maintenance embodies continuous improvement and care of assets to ensure that their operation at optimum efficiency becomes an organizational value driver.
One of its objectives is reducing an overall production cost, including how cost saving happened by finding the root causes of machine worn out and failure, then implement a precise and proactive countermeasure (Uche, 2011).
From the TPM point of view, 6 big losses are to be found in the MedCorp B. V. Beilen. 1. Failures with the sturns in the Cilco machines, which make the whole line stop. These unplannend failures are handeled by the maintenance, but take a lot of precious time (and with that capacity is lost).
This is 24 hours of “doing nothing” for the operators, and 24 hours of work done by the maintenance.
This lost profit is € 720. 000,- it is medicine you cannot make at that moment (24 hours * 1. 5 kilos * €20. 000).
Actually, this holds two problems; the time it takes for the reperation once the maintenance is there, and the time that is needed for the operators to find the problem and warn the maintenance before! 2. Unplanned downtime by Change-over/set-ups of the Cilco machines. Change-over/set-ups are incredibly high! In 2 weeks, the company lost 21 hours due to this. This is almost 4 % of the total capacity of all the machines. It carries lost profit of € 630. 000,- (21 hours * 1. kilos * €20. 000).
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3. Operating errors causing failures to the Cilco machines (Unplanned downtime) In two weeks, 13 hours the capacity of the machine was lost due to stoppages in which the maintenance did not play any role, so under supervision of the operator. Most of these accidents were due to mistakes of the operators. This carries lost profit of € 390. 000,- (1,5 kilos per hour * 13 lost hours * € 20. 000 costs of the medicine).
4. Wasted materials – Quality Medicine as well as packaging material is often wasted during efforts to start up the machines after changeovers and set-ups.
In total, 5% of the assembly throughput had to be destroyed as a result of this during the measurement period. From time to time, the assembly capacity is all together insufficient which has extensive financial consequences because of the high value of the medicine. 5. Culture on the workfloor Production and maintenance staff frequently point at each other if these things do not go as planned. This is, in my opinion, a big problem for solving all the mess with the machines. The operators need the maintenance and the other way around.
The way of communicating and working together is key to the success of the plant. The machines typically produce at a lesser speed than they should. According to the supplier, the four Cilco’s should together be able to package 750 packages (paper boxes) per hour. One paper box with packaged product contains on average 8 grams of the product, so that in theory 6 kilos of the product can be packaged per hour. However, recent measurements consistently indicate that normally, the four lines produce at a rate of 500 packages (paper boxes) per hour. This means a total cost of € 6 millionon a basis of 2 weeks! Yearly this means € 156 million of lost profit! (250 packages per hour short on capacity * 0,008 kilo * € 20. 000 * (10 days*2 shifts * 7,5 workhours)) 4 Maintenance Management MTTR & MTBF In the picture below, the terms Mean Time Between Failures (MTBF) and Mean Time to Repair (MTTR), are graphed3. In the tables below, you will find these measures for the current situation. Failures, handled by maintencance MTTR MTBF 6,0 3,0 5,8 62,2 6,2 18,8 6,0 Failure 1 2 3 4 day 4 5 9 10 hour 8 1 5 14 Failure 1 2 3 4 5 6 7 8 ay 1 2 3 4 5 6 9 10 hour 8 10 4 8 1 7 5 14 Failures, handled by operators Failures, handled by maintencance MTTR MTBF 3 15,0 3 7,0 4 16,0 6,0 3,0 5,8 16,2 3,0 43,0 6,2 18,8 6,0 5 The Overall Equipment Effectiveness (OEE) OEE is frequently used as a key metric in TPM gives a consistent way to measure the effectiveness of TPM and other initiatives by providing an overall framework for measuring production efficiency4. OEE is a “best practices” way to monitor and improve the effectiveness of your manufacturing processes (i. e. machines, manufacturing cells, assembly ines).
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OEE is simple and practical. It takes the most common and important sources of manufacturing productivity loss, places them into three primary categories and distills them into metrics that provide an excellent gauge for measuring where you are and how you can improve! The beauty of OEE is not that it gives you one magic number; it’s that it gives you three numbers, which are all useful individually as your situation changes from day to day. OEE truly reduces complex production problems into simple, intuitive presentation of information.
It helps you systematically improve your process with easy-to-obtain measurements (Vorne Industries, 2008).
OEE = availability * performance * quality Availability takes into account Down Time Loss, and is calculated as: Performance takes into account Speed Loss, and is calculated as: Quality takes into account Quality Loss, and is calculated as: Availability = Operating Time / Planned Production Time Performance = (Total Pieces / Operating Time) / Ideal Run Rate Quality = (% of goods good ( = %total – %waste))/(% of total goods)
Calculations are shown below: Current situation* Availability 61% Performance (per hour) 67% Quality 95% OEE 39% * Assumed is that 1 shift consists of 7,5 hours, because of the planned downtime due to breaks for the operators Looking at the calculations above, it may be clear that the priority for improvement is to be in availability and performance! continuous process Notice the following: Current capacity continuous process (50 till 60 kg/day): 100 %* of the medicine (powder from continuous process) can currently, on average, be packaged per day, if you have zero down-time!!!
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Full capacity continuous process (85 kg/day) 70 % of of the medicine (powder from continuous process) could currently, on average, be packaged per day, if you have zero down-time!!! *(= (capacity of the packaging process / (medicine, powder from continuous process, kg )*100%)) This means, that optimizing the discrete production of the factory, will have no use if the continuous process is not operated in a higher capacity aswell! Because: If the medicine (i. e. the powder from the continuous process factory) is not packaged, then it almost immediately becomes obsolete. The next bottleneck will be the continuous process (after optimizing the discrete production).
? It is important to optimize the continuous process in accordance to the discrete production to prevent waste of precious medicine. As is known that, the market for this medicine is very good and growing. Achieving a higher capacity will enable your firm to reap what you sow! 6 Quick wins 1. By working more accurate, it can easily be prevented that operators make mistakes. This can even be a simple “check”, carried out by a second pair of eyes, before pushing the start-button of the Cilco.
This would raise the availability in the OEE substantially. 2. Schedule more downtime for maintenance. If you expect the sturns in the Cilcos to break-down on a regular basis, repair them on forehand. If this is done in other scheduled downtime (i. e. lunchbreaks or change-over and set-up time) you can efficiently do maintenance at the same time. A proposal is to schedule change-over, set-up time, and lunchbreaks in a sufficient way, to check the sturns/machines and refurbish the sturns if needed in these timeslots.
This will save a lot of time (the operators don’t need to call out for the maintenance, they will be there already), and the maintenance department will have a better scheduled, less stressfull workday. Therefore they will be able to work more efficiently on all the other tasks. 3. Another option contributing to the above, is to have the operators check the machines on potential breakdowns in the future. If you train the operators to recognize and find signs of future failure, and if possible, even perform simple maintenance tasks, this will improve the performance and availability.
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Also, this will reduce the mean time to repair! Current Organizations Structure In the current situation, that the employees in Nottingham do the engineering part (this involves both the initial design of all production equipment and so-called ‘maintenance engineering’, i. e. analyzing the production equipment and recommending small and large improvements).
This might cause some ineffective decision making. These important desions might better be done bottom-up.
A proposal might be to send employees from Nottingham to Beilen, so that they can look at the process directly and better make the decisions on topics that matter (Keen & Sol, 2008).
Another solution is to send this responsibility for the engineering to a manager in Beilen itself. This more bottom-up way of decision making (straight from the practice on the plant) may also help better the attitude of the operators (bottom) towards the management, ass will more authority and variety in the tasks the operators perform (see point 3, addressed in the Quick Wins chapter).
Enhancing the collaboration between the maintentance department and the operators can also enhance the efficiency of the maintenance ass addressed before. The current directive way of management might also not be applicable to the situation anymore. If situational leadership is carried out, the employees will perform better. For example, a case study, in AkzoNobel’s plant in Heiligerlee this leadership enhances the development of the individual employee and encourages them to come up with ideas for performance improvement.
This situational leadership can be brought in to the company by providing workshops for the production manager. Other improvements If the lunch-breaks are done in two shifts (6 employees at the time for a break), the machines can keep on running and the availability will go up. Increase the capacity of the continuous process according to the increasing of the discrete production, this is essential. Continuously measure (day by day, week by week) the productivity of the discrete production using measurements like the OEE.
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Reward good work; o Encourage your employees (operators) by rewarding them on zero-failure (due to operator mistakes) weeks. This can be done in a simple way: the top 3 employers with the longest streak of failure-free-shifts will be rewarded in the form of free lunch or mentioning them in a weekly newspaper. o Also provide information to the employees about the MTTR and MTBF, for example, a graph of these measurements on a timeline in the canteen. 7 Possible business case proposal Below, you will find an overview of the achievable situation, if you implement the changes mentioned in this document before.
Reduce the setup and change-over time to 1 hour a day, by introducing a smaller product variety to your costumers and give them discounts when they will order on a longer term ahead. This will be a task on itself which will need to be a responsibility for one of your employees. Reduce the mean time to repair to 1 hour, see nr. 2 and 3 of the quick wins. It is also possible to scale up the performance. Contact the supplier that the product does not do what is is told. Ask for new machines or financial compensation, whether something else.
In this case it is assumed that the performance is to be upgraded to 600 packages per hour. Scheduled set-up/change-over time including maintenance New situation Day Hour MTTR MTBF 1 4 1 1 12 1 2 4 1 2 12 1 3 4 1 3 12 1 4 4 1 4 12 1 5 4 1 5 12 1 6 4 1 6 12 1 7 4 1 7 12 1 8 4 1 8 12 1 9 4 1 9 12 1 10 4 1 10 12 1 * this set-up and change-over time is in the break (a two shift break of 2 times 30 min) 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Availability Performance (per hour) Quality OEE Current situation* New situation 61% 67% 95% 39% 97% 80% 95% 74%
On the next page you will find an overview of a possible scheme to implement most of the mentioned improvements. 8 Week 0 Organize a dinner to announce the change! Invite all the employees to this formal dinner, the plant manager and a manager from Nottingham will make clear the current situation and will have to make clear why there is a need for change. Also, the need for change must be encouraged during the whole project. Here you set the goals for the MTTR and frequency and length of setup-time/changeovertime. Implicit a ‘double-check’! Carried out by a second pair of eyes, before pushing the start-button of the Cilco.
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This would raise the availability in the OEE substantially. Start workshops for the production manager towards situational leadership. This can be provided by an external company, and contain of multiple sessions. Have the operators be trained for more technical knowledge about the machines. This can be provided by the maintenance department, and contain of multiple sessions. Start locating the responsibility for the engineering at Beilen. Compromise a plan for doing this, either bring Nottingham to Beilen or another way. Schedule downtime for lunchbreaks or change-over and set-up time.
Schedule change-over, set-up time, and lunch breaks in a sufficient way, to check the sturns/machines and refurbish the sturns if needed in these timeslots. Meeting for all managers and some operators and some of maintenance This meeting is needed to measure the development of the implications in the precious week(s), it is also necessary to communicate and steer to the right direction. Adapt the continuous process to the improvements on the discrete production. Measure the accomplishments of the previous week(s) and raise the capacity towards the predicted capacity of the discrete production.
Meeting for all managers and some operators and some of maintenance This meeting is needed to measure the development of the implications in the precious week(s), it is also necessary to communicate and steer to the right direction. Adapt the continuous process to the improvements on the discrete production. Measure the accomplishments of the previous week(s) and raise the capacity towards the predicted capacity of the discrete production. Introduce a schedule for checks to be carried out by the operators to locate potential future breakdowns. This will be a hard part, this will have to be in cooperation with the maintenance department.
This can be seen as a new way of working. It will be necessary to set up a “guide” for this project. All the employees must know what to do and what will change. The production manager will be able to take responsibility for this process (he must start at week 1 to prepare all the work).
Meeting for all managers and some operators and some of maintenance This meeting is needed to measure the development of the implications in the precious week(s), it is also necessary to communicate and steer to the right direction. Adapt the continuous process to the improvements on the discrete production.
Measure the accomplishments of the previous week(s) and raise the capacity towards the predicted capacity of the discrete production. Meeting for all managers and some operators and some of maintenance This …. direction. Adapt the continuous process to the improvements on the discrete production. Measure … production. Meeting for all managers and some operators and some of maintenance This … direction. Adapt the continuous process to the improvements on the discrete production. Measure … production. Meeting for all managers and some operators and some of maintenance This … direction.
Adapt the continuous process to the improvements on the discrete production. Measure … production. Meeting for all managers and some operators and some of maintenance This … direction. Adapt the continuous process to the improvements on the discrete production. Measure … production. Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 and on.. 9 References Brah, S. A. , & Chong, W. K. ,2004. Relationship between total productive maintenance and performance. International Journal of Production Research, 42(12), 2383–2401. Chulhyun K. , Hakyeon L. , Jeonghwan J. , 2011. Measuring