Forum help

I think it is up to Maintenance Managers to align their objectives to the overall corporate objectives and learn to "speak the language" of business. Learn to understand budgets, balance sheets, cash flow statements, and be able to describe your team's impact on them. It is the role of the manager to translate HIS KPI's of Uptime improvement into the language of "additional available production time". I always hear that additional uptime doesn't matter if you're not sold out....well not being sold out is a KPI problem for the sales and marketing side of the business. You provide the opportunity, leave it to others to take advantage of it. The Maintenance Manager should also be able to explain to the maintenance team how their performance indicators translate to financial results for the organization. The Maintenance Manager needs to be able to calculate and present what the ROI is for proposed projects. In other words, Maintenance Managers need to become financially educated. I am fortunate as I left my "technical track" after completion of my Associate's Degree in Nuclear Technology (I am a retired Navy Nuke), and finished a BS degree in Management, so I got the full financial education that comes with that. I was somewhat of a Unicorn in the maintenance world. 

I think it is up to Maintenance Managers to align their objectives to the overall corporate objectives and learn to "speak the language" of business. Learn to understand budgets, balance sheets, cash flow statements, and be able to describe your team's impact on them. It is the role of the manager to translate HIS KPI's of Uptime improvement into the language of "additional available production time". I always hear that additional uptime doesn't matter if you're not sold out....well not being sold out is a KPI problem for the sales and marketing side of the business. You provide the opportunity, leave it to others to take advantage of it. The Maintenance Manager should also be able to explain to the maintenance team how their performance indicators translate to financial results for the organization. The Maintenance Manager needs to be able to calculate and present what the ROI is for proposed projects. In other words, Maintenance Managers need to become financially educated. I am fortunate as I left my "technical track" after completion of my Associate's Degree in Nuclear Technology (I am a retired Navy Nuke), and finished a BS degree in Management, so I got the full financial education that comes with that. I was somewhat of a Unicorn in the maintenance world. 

I think it is up to Maintenance Managers to align their objectives to the overall corporate objectives and learn to "speak the language" of business. Learn to understand budgets, balance sheets, cash flow statements, and be able to describe your team's impact on them. It is the role of the manager to translate HIS KPI's of Uptime improvement into the language of "additional available production time". I always hear that additional uptime doesn't matter if you're not sold out....well not being sold out is a KPI problem for the sales and marketing side of the business. You provide the opportunity, leave it to others to take advantage of it. The Maintenance Manager should also be able to explain to the maintenance team how their performance indicators translate to financial results for the organization. The Maintenance Manager needs to be able to calculate and present what the ROI is for proposed projects. In other words, Maintenance Managers need to become financially educated. I am fortunate as I left my "technical track" after completion of my Associate's Degree in Nuclear Technology (I am a retired Navy Nuke), and finished a BS degree in Management, so I got the full financial education that comes with that. I was somewhat of a Unicorn in the maintenance world. 

Been sharing with you Vic for a long time, meanwhile you was  in  charge to direct the efforts to implement the right reliability kpi´s globally in our company, it takes years to achieved it,   I am sure that  you leave your mark !!!   because  we continue doing well!

Best Regards
David

I so agree with this Vic. I started a process with a man at the Zurich University of Applied Sciences. He specialises in finding the links between different primary parameters and its money effects. We tried to find good links between the normal parameters found in maintenance, and the size of the budget. But it was difficult to get meaningful relationships. If there are anyone out there that has insights regarding this, I would love to take that process up again. 

NIST addressed this a few years ago in a joint SMRP government relations project: Economics of Manufacturing Machinery Maintenance (link opens in new window) as part of the 'Manufacturing Machinery Maintenance' project (opens in new window).  They reviewed and tied corporate KPI to maintenance activities including maintenance costs, preventable losses, and benefits of advanced maintenance strategies.  They were also able to relate the following (from NIST web page):

Maintenance Costs: 2016 Machinery maintenance expenditures for NAICS 321-339 (excluding 324 and 325) were estimated to be $57.3 billion. Additional expenditures due to faults and failures were estimated at $16.3 billion and costs for inventory to buffer against maintenance issues costed $0.9 billion. In total, these maintenance activities costed $74.5 billion.

Preventable Losses: The 2016 losses due to preventable maintenance issues amounted to $119.1 billion: $18.1 billion due to downtime, $0.8 billion due to defects, and $100.2 billion due to lost sales from delays and defects. Additionally, an estimated 16.03 injuries and 0.05 deaths per million employees were associated with these maintenance issues.

Benefits of Advanced Maintenance Strategies: The estimated 2016 perceived benefit of adopting some additional amount of predictive maintenance was $6.5 billion from downtime reduction and $67.3 billion in increased sales ($73.8 billion in total). Other perceived benefits such as reduced defects are also likely to occur but were not monetized.

The top 25 % of those establishments relying on reactive maintenance was associated with 3.3 times more downtime than those in the bottom 25 %. They were also associated with 16.0 times more defects, 2.8 more lost sales due to defects from maintenance, 2.4 times more lost sales due to delays from maintenance, and 4.9 times more inventory increases due to maintenance issues. On average, 45.7 % of machinery maintenance was reactive maintenance. Those who relied less on reactive maintenance, and more on preventive and/or predictive maintenance, were more likely to use a pull (i.e., make to order) stock strategy and tend to be differentiators as opposed to being a cost competitor. That is, they rely more on their reputation and produce products on demand. The implication being that reactive maintenance reduces quality and increases uncertainty in production time.

Among those establishments that primarily rely on preventive and predictive maintenance (i.e., less than 50 % reactive maintenance), the top 50 % in predictive maintenance was associated with 15 % less downtime, an 87 % lower defect rate, and 66 % less inventory increases due to unplanned maintenance. Those establishments that relied more on predictive maintenance than preventive were more likely to have a pull (i.e., make to order) stock strategy and more likely to be a differentiator as opposed to being a cost competitor. Moreover, predictive maintenance is associated with higher quality products and shorter production times through reduced downtime. For those establishments that invested more heavily into preventive or predictive.

In addition, in tying our work on project implementation with our industry partners we tie energy and emissions (energy in general, emissions with companies that have ESG goals) to the activity.  These are measurable values and maintenance activities were identified by the US Department of Energy in the 1990s as the number one method for decreasing energy spend by a corporation.  Rutgers University energy extension center and the University of Illinois' Energy Resources Center identified a minimum energy reduction of 14% just through the application of a maintenance program from a reactive maintenance program.  This was later implemented at the National Institutes of Health CUP with a combined predictive/preventive condition-based program on boiler and chiller systems with a resulting impact of ~50% reduction in overall energy spend (electric, gas, water) and was also proven with the US DOE's commercial/industrial 'Save Energy Now' program that started in 2005-2010(ish).  The tools available for that program (developed starting in 1993-present) can be found: software tools, including MEASUR; Link to all other case studies, manuals, tools, etc.  The initial impact of the Save Energy Now program at General Motors in the area of steam and energy, for instance, can be found on P. 42 of the August 2006 edition of Uptime Magazine (link here in separate window).

Just some food for thought on this topic.

I so agree with this Vic. I started a process with a man at the Zurich University of Applied Sciences. He specialises in finding the links between different primary parameters and its money effects. We tried to find good links between the normal parameters found in maintenance, and the size of the budget. But it was difficult to get meaningful relationships. If there are anyone out there that has insights regarding this, I would love to take that process up again. 

NIST addressed this a few years ago in a joint SMRP government relations project: Economics of Manufacturing Machinery Maintenance (link opens in new window) as part of the 'Manufacturing Machinery Maintenance' project (opens in new window).  They reviewed and tied corporate KPI to maintenance activities including maintenance costs, preventable losses, and benefits of advanced maintenance strategies.  They were also able to relate the following (from NIST web page):

Maintenance Costs: 2016 Machinery maintenance expenditures for NAICS 321-339 (excluding 324 and 325) were estimated to be $57.3 billion. Additional expenditures due to faults and failures were estimated at $16.3 billion and costs for inventory to buffer against maintenance issues costed $0.9 billion. In total, these maintenance activities costed $74.5 billion.

Preventable Losses: The 2016 losses due to preventable maintenance issues amounted to $119.1 billion: $18.1 billion due to downtime, $0.8 billion due to defects, and $100.2 billion due to lost sales from delays and defects. Additionally, an estimated 16.03 injuries and 0.05 deaths per million employees were associated with these maintenance issues.

Benefits of Advanced Maintenance Strategies: The estimated 2016 perceived benefit of adopting some additional amount of predictive maintenance was $6.5 billion from downtime reduction and $67.3 billion in increased sales ($73.8 billion in total). Other perceived benefits such as reduced defects are also likely to occur but were not monetized.

The top 25 % of those establishments relying on reactive maintenance was associated with 3.3 times more downtime than those in the bottom 25 %. They were also associated with 16.0 times more defects, 2.8 more lost sales due to defects from maintenance, 2.4 times more lost sales due to delays from maintenance, and 4.9 times more inventory increases due to maintenance issues. On average, 45.7 % of machinery maintenance was reactive maintenance. Those who relied less on reactive maintenance, and more on preventive and/or predictive maintenance, were more likely to use a pull (i.e., make to order) stock strategy and tend to be differentiators as opposed to being a cost competitor. That is, they rely more on their reputation and produce products on demand. The implication being that reactive maintenance reduces quality and increases uncertainty in production time.

Among those establishments that primarily rely on preventive and predictive maintenance (i.e., less than 50 % reactive maintenance), the top 50 % in predictive maintenance was associated with 15 % less downtime, an 87 % lower defect rate, and 66 % less inventory increases due to unplanned maintenance. Those establishments that relied more on predictive maintenance than preventive were more likely to have a pull (i.e., make to order) stock strategy and more likely to be a differentiator as opposed to being a cost competitor. Moreover, predictive maintenance is associated with higher quality products and shorter production times through reduced downtime. For those establishments that invested more heavily into preventive or predictive.

In addition, in tying our work on project implementation with our industry partners we tie energy and emissions (energy in general, emissions with companies that have ESG goals) to the activity.  These are measurable values and maintenance activities were identified by the US Department of Energy in the 1990s as the number one method for decreasing energy spend by a corporation.  Rutgers University energy extension center and the University of Illinois' Energy Resources Center identified a minimum energy reduction of 14% just through the application of a maintenance program from a reactive maintenance program.  This was later implemented at the National Institutes of Health CUP with a combined predictive/preventive condition-based program on boiler and chiller systems with a resulting impact of ~50% reduction in overall energy spend (electric, gas, water) and was also proven with the US DOE's commercial/industrial 'Save Energy Now' program that started in 2005-2010(ish).  The tools available for that program (developed starting in 1993-present) can be found: software tools, including MEASUR; Link to all other case studies, manuals, tools, etc.  The initial impact of the Save Energy Now program at General Motors in the area of steam and energy, for instance, can be found on P. 42 of the August 2006 edition of Uptime Magazine (link here in separate window).

Just some food for thought on this topic.

I so agree with this Vic. I started a process with a man at the Zurich University of Applied Sciences. He specialises in finding the links between different primary parameters and its money effects. We tried to find good links between the normal parameters found in maintenance, and the size of the budget. But it was difficult to get meaningful relationships. If there are anyone out there that has insights regarding this, I would love to take that process up again. 

Hello All - this is an area in which I have been intimately active, with a good degree of success, for decades. I include below copies of slides presented in 2003 at a conference in Durban, South Africa around "Business Centric Maintenance". In my experience, trying to speak to Boards, or Executive Committees in "Technical Speak" inevitably leads to failure. It is a fundamental key to success to develop the capability to address Boards and Executive Committees in language that they understand! A) They do not understand "Technical Speak", B) They have no desire to understand "Technical Speak", and C) When "Technical Speak" is introduced, the majority of them switch-off!

Over my career I headed up maintenance and technical departments in various areas of business, and ran all of them as SBU's! As a result I was able, in all cases, to motivate their contribution to the financial bottom line, as well as having developed long term predictive asset performance models that Boards and ExCo's not only to a large degree embraced, but often also took ownership of and the support garnered in getting them to understand the dynamic tension between funding, asset associated risk, and levels of asset performance became straight-forward - see training slide below:

To avoid tugs' of war:

I hope this helps in the discussions - it can be achieved and in my Asset Management and Operational Leadership training courses I present several case studies of where it has been achieved in practice.

Best wishes, John Doran.

NIST addressed this a few years ago in a joint SMRP government relations project: Economics of Manufacturing Machinery Maintenance (link opens in new window) as part of the 'Manufacturing Machinery Maintenance' project (opens in new window).  They reviewed and tied corporate KPI to maintenance activities including maintenance costs, preventable losses, and benefits of advanced maintenance strategies.  They were also able to relate the following (from NIST web page):

Maintenance Costs: 2016 Machinery maintenance expenditures for NAICS 321-339 (excluding 324 and 325) were estimated to be $57.3 billion. Additional expenditures due to faults and failures were estimated at $16.3 billion and costs for inventory to buffer against maintenance issues costed $0.9 billion. In total, these maintenance activities costed $74.5 billion.

Preventable Losses: The 2016 losses due to preventable maintenance issues amounted to $119.1 billion: $18.1 billion due to downtime, $0.8 billion due to defects, and $100.2 billion due to lost sales from delays and defects. Additionally, an estimated 16.03 injuries and 0.05 deaths per million employees were associated with these maintenance issues.

Benefits of Advanced Maintenance Strategies: The estimated 2016 perceived benefit of adopting some additional amount of predictive maintenance was $6.5 billion from downtime reduction and $67.3 billion in increased sales ($73.8 billion in total). Other perceived benefits such as reduced defects are also likely to occur but were not monetized.

The top 25 % of those establishments relying on reactive maintenance was associated with 3.3 times more downtime than those in the bottom 25 %. They were also associated with 16.0 times more defects, 2.8 more lost sales due to defects from maintenance, 2.4 times more lost sales due to delays from maintenance, and 4.9 times more inventory increases due to maintenance issues. On average, 45.7 % of machinery maintenance was reactive maintenance. Those who relied less on reactive maintenance, and more on preventive and/or predictive maintenance, were more likely to use a pull (i.e., make to order) stock strategy and tend to be differentiators as opposed to being a cost competitor. That is, they rely more on their reputation and produce products on demand. The implication being that reactive maintenance reduces quality and increases uncertainty in production time.

Among those establishments that primarily rely on preventive and predictive maintenance (i.e., less than 50 % reactive maintenance), the top 50 % in predictive maintenance was associated with 15 % less downtime, an 87 % lower defect rate, and 66 % less inventory increases due to unplanned maintenance. Those establishments that relied more on predictive maintenance than preventive were more likely to have a pull (i.e., make to order) stock strategy and more likely to be a differentiator as opposed to being a cost competitor. Moreover, predictive maintenance is associated with higher quality products and shorter production times through reduced downtime. For those establishments that invested more heavily into preventive or predictive.

In addition, in tying our work on project implementation with our industry partners we tie energy and emissions (energy in general, emissions with companies that have ESG goals) to the activity.  These are measurable values and maintenance activities were identified by the US Department of Energy in the 1990s as the number one method for decreasing energy spend by a corporation.  Rutgers University energy extension center and the University of Illinois' Energy Resources Center identified a minimum energy reduction of 14% just through the application of a maintenance program from a reactive maintenance program.  This was later implemented at the National Institutes of Health CUP with a combined predictive/preventive condition-based program on boiler and chiller systems with a resulting impact of ~50% reduction in overall energy spend (electric, gas, water) and was also proven with the US DOE's commercial/industrial 'Save Energy Now' program that started in 2005-2010(ish).  The tools available for that program (developed starting in 1993-present) can be found: software tools, including MEASUR; Link to all other case studies, manuals, tools, etc.  The initial impact of the Save Energy Now program at General Motors in the area of steam and energy, for instance, can be found on P. 42 of the August 2006 edition of Uptime Magazine (link here in separate window).

Just some food for thought on this topic.

I so agree with this Vic. I started a process with a man at the Zurich University of Applied Sciences. He specialises in finding the links between different primary parameters and its money effects. We tried to find good links between the normal parameters found in maintenance, and the size of the budget. But it was difficult to get meaningful relationships. If there are anyone out there that has insights regarding this, I would love to take that process up again. 

Hello All - this is an area in which I have been intimately active, with a good degree of success, for decades. I include below copies of slides presented in 2003 at a conference in Durban, South Africa around "Business Centric Maintenance". In my experience, trying to speak to Boards, or Executive Committees in "Technical Speak" inevitably leads to failure. It is a fundamental key to success to develop the capability to address Boards and Executive Committees in language that they understand! A) They do not understand "Technical Speak", B) They have no desire to understand "Technical Speak", and C) When "Technical Speak" is introduced, the majority of them switch-off!

Over my career I headed up maintenance and technical departments in various areas of business, and ran all of them as SBU's! As a result I was able, in all cases, to motivate their contribution to the financial bottom line, as well as having developed long term predictive asset performance models that Boards and ExCo's not only to a large degree embraced, but often also took ownership of and the support garnered in getting them to understand the dynamic tension between funding, asset associated risk, and levels of asset performance became straight-forward - see training slide below:

To avoid tugs' of war:

I hope this helps in the discussions - it can be achieved and in my Asset Management and Operational Leadership training courses I present several case studies of where it has been achieved in practice.

Best wishes, John Doran.

NIST addressed this a few years ago in a joint SMRP government relations project: Economics of Manufacturing Machinery Maintenance (link opens in new window) as part of the 'Manufacturing Machinery Maintenance' project (opens in new window).  They reviewed and tied corporate KPI to maintenance activities including maintenance costs, preventable losses, and benefits of advanced maintenance strategies.  They were also able to relate the following (from NIST web page):

Maintenance Costs: 2016 Machinery maintenance expenditures for NAICS 321-339 (excluding 324 and 325) were estimated to be $57.3 billion. Additional expenditures due to faults and failures were estimated at $16.3 billion and costs for inventory to buffer against maintenance issues costed $0.9 billion. In total, these maintenance activities costed $74.5 billion.

Preventable Losses: The 2016 losses due to preventable maintenance issues amounted to $119.1 billion: $18.1 billion due to downtime, $0.8 billion due to defects, and $100.2 billion due to lost sales from delays and defects. Additionally, an estimated 16.03 injuries and 0.05 deaths per million employees were associated with these maintenance issues.

Benefits of Advanced Maintenance Strategies: The estimated 2016 perceived benefit of adopting some additional amount of predictive maintenance was $6.5 billion from downtime reduction and $67.3 billion in increased sales ($73.8 billion in total). Other perceived benefits such as reduced defects are also likely to occur but were not monetized.

The top 25 % of those establishments relying on reactive maintenance was associated with 3.3 times more downtime than those in the bottom 25 %. They were also associated with 16.0 times more defects, 2.8 more lost sales due to defects from maintenance, 2.4 times more lost sales due to delays from maintenance, and 4.9 times more inventory increases due to maintenance issues. On average, 45.7 % of machinery maintenance was reactive maintenance. Those who relied less on reactive maintenance, and more on preventive and/or predictive maintenance, were more likely to use a pull (i.e., make to order) stock strategy and tend to be differentiators as opposed to being a cost competitor. That is, they rely more on their reputation and produce products on demand. The implication being that reactive maintenance reduces quality and increases uncertainty in production time.

Among those establishments that primarily rely on preventive and predictive maintenance (i.e., less than 50 % reactive maintenance), the top 50 % in predictive maintenance was associated with 15 % less downtime, an 87 % lower defect rate, and 66 % less inventory increases due to unplanned maintenance. Those establishments that relied more on predictive maintenance than preventive were more likely to have a pull (i.e., make to order) stock strategy and more likely to be a differentiator as opposed to being a cost competitor. Moreover, predictive maintenance is associated with higher quality products and shorter production times through reduced downtime. For those establishments that invested more heavily into preventive or predictive.

In addition, in tying our work on project implementation with our industry partners we tie energy and emissions (energy in general, emissions with companies that have ESG goals) to the activity.  These are measurable values and maintenance activities were identified by the US Department of Energy in the 1990s as the number one method for decreasing energy spend by a corporation.  Rutgers University energy extension center and the University of Illinois' Energy Resources Center identified a minimum energy reduction of 14% just through the application of a maintenance program from a reactive maintenance program.  This was later implemented at the National Institutes of Health CUP with a combined predictive/preventive condition-based program on boiler and chiller systems with a resulting impact of ~50% reduction in overall energy spend (electric, gas, water) and was also proven with the US DOE's commercial/industrial 'Save Energy Now' program that started in 2005-2010(ish).  The tools available for that program (developed starting in 1993-present) can be found: software tools, including MEASUR; Link to all other case studies, manuals, tools, etc.  The initial impact of the Save Energy Now program at General Motors in the area of steam and energy, for instance, can be found on P. 42 of the August 2006 edition of Uptime Magazine (link here in separate window).

Just some food for thought on this topic.

I so agree with this Vic. I started a process with a man at the Zurich University of Applied Sciences. He specialises in finding the links between different primary parameters and its money effects. We tried to find good links between the normal parameters found in maintenance, and the size of the budget. But it was difficult to get meaningful relationships. If there are anyone out there that has insights regarding this, I would love to take that process up again. 

Hello All - this is an area in which I have been intimately active, with a good degree of success, for decades. I include below copies of slides presented in 2003 at a conference in Durban, South Africa around "Business Centric Maintenance". In my experience, trying to speak to Boards, or Executive Committees in "Technical Speak" inevitably leads to failure. It is a fundamental key to success to develop the capability to address Boards and Executive Committees in language that they understand! A) They do not understand "Technical Speak", B) They have no desire to understand "Technical Speak", and C) When "Technical Speak" is introduced, the majority of them switch-off!

Over my career I headed up maintenance and technical departments in various areas of business, and ran all of them as SBU's! As a result I was able, in all cases, to motivate their contribution to the financial bottom line, as well as having developed long term predictive asset performance models that Boards and ExCo's not only to a large degree embraced, but often also took ownership of and the support garnered in getting them to understand the dynamic tension between funding, asset associated risk, and levels of asset performance became straight-forward - see training slide below:

To avoid tugs' of war:

I hope this helps in the discussions - it can be achieved and in my Asset Management and Operational Leadership training courses I present several case studies of where it has been achieved in practice.

Best wishes, John Doran.

NIST addressed this a few years ago in a joint SMRP government relations project: Economics of Manufacturing Machinery Maintenance (link opens in new window) as part of the 'Manufacturing Machinery Maintenance' project (opens in new window).  They reviewed and tied corporate KPI to maintenance activities including maintenance costs, preventable losses, and benefits of advanced maintenance strategies.  They were also able to relate the following (from NIST web page):

Maintenance Costs: 2016 Machinery maintenance expenditures for NAICS 321-339 (excluding 324 and 325) were estimated to be $57.3 billion. Additional expenditures due to faults and failures were estimated at $16.3 billion and costs for inventory to buffer against maintenance issues costed $0.9 billion. In total, these maintenance activities costed $74.5 billion.

Preventable Losses: The 2016 losses due to preventable maintenance issues amounted to $119.1 billion: $18.1 billion due to downtime, $0.8 billion due to defects, and $100.2 billion due to lost sales from delays and defects. Additionally, an estimated 16.03 injuries and 0.05 deaths per million employees were associated with these maintenance issues.

Benefits of Advanced Maintenance Strategies: The estimated 2016 perceived benefit of adopting some additional amount of predictive maintenance was $6.5 billion from downtime reduction and $67.3 billion in increased sales ($73.8 billion in total). Other perceived benefits such as reduced defects are also likely to occur but were not monetized.

The top 25 % of those establishments relying on reactive maintenance was associated with 3.3 times more downtime than those in the bottom 25 %. They were also associated with 16.0 times more defects, 2.8 more lost sales due to defects from maintenance, 2.4 times more lost sales due to delays from maintenance, and 4.9 times more inventory increases due to maintenance issues. On average, 45.7 % of machinery maintenance was reactive maintenance. Those who relied less on reactive maintenance, and more on preventive and/or predictive maintenance, were more likely to use a pull (i.e., make to order) stock strategy and tend to be differentiators as opposed to being a cost competitor. That is, they rely more on their reputation and produce products on demand. The implication being that reactive maintenance reduces quality and increases uncertainty in production time.

Among those establishments that primarily rely on preventive and predictive maintenance (i.e., less than 50 % reactive maintenance), the top 50 % in predictive maintenance was associated with 15 % less downtime, an 87 % lower defect rate, and 66 % less inventory increases due to unplanned maintenance. Those establishments that relied more on predictive maintenance than preventive were more likely to have a pull (i.e., make to order) stock strategy and more likely to be a differentiator as opposed to being a cost competitor. Moreover, predictive maintenance is associated with higher quality products and shorter production times through reduced downtime. For those establishments that invested more heavily into preventive or predictive.

In addition, in tying our work on project implementation with our industry partners we tie energy and emissions (energy in general, emissions with companies that have ESG goals) to the activity.  These are measurable values and maintenance activities were identified by the US Department of Energy in the 1990s as the number one method for decreasing energy spend by a corporation.  Rutgers University energy extension center and the University of Illinois' Energy Resources Center identified a minimum energy reduction of 14% just through the application of a maintenance program from a reactive maintenance program.  This was later implemented at the National Institutes of Health CUP with a combined predictive/preventive condition-based program on boiler and chiller systems with a resulting impact of ~50% reduction in overall energy spend (electric, gas, water) and was also proven with the US DOE's commercial/industrial 'Save Energy Now' program that started in 2005-2010(ish).  The tools available for that program (developed starting in 1993-present) can be found: software tools, including MEASUR; Link to all other case studies, manuals, tools, etc.  The initial impact of the Save Energy Now program at General Motors in the area of steam and energy, for instance, can be found on P. 42 of the August 2006 edition of Uptime Magazine (link here in separate window).

Just some food for thought on this topic.

I so agree with this Vic. I started a process with a man at the Zurich University of Applied Sciences. He specialises in finding the links between different primary parameters and its money effects. We tried to find good links between the normal parameters found in maintenance, and the size of the budget. But it was difficult to get meaningful relationships. If there are anyone out there that has insights regarding this, I would love to take that process up again. 

Hello All - this is an area in which I have been intimately active, with a good degree of success, for decades. I include below copies of slides presented in 2003 at a conference in Durban, South Africa around "Business Centric Maintenance". In my experience, trying to speak to Boards, or Executive Committees in "Technical Speak" inevitably leads to failure. It is a fundamental key to success to develop the capability to address Boards and Executive Committees in language that they understand! A) They do not understand "Technical Speak", B) They have no desire to understand "Technical Speak", and C) When "Technical Speak" is introduced, the majority of them switch-off!

Over my career I headed up maintenance and technical departments in various areas of business, and ran all of them as SBU's! As a result I was able, in all cases, to motivate their contribution to the financial bottom line, as well as having developed long term predictive asset performance models that Boards and ExCo's not only to a large degree embraced, but often also took ownership of and the support garnered in getting them to understand the dynamic tension between funding, asset associated risk, and levels of asset performance became straight-forward - see training slide below:

To avoid tugs' of war:

I hope this helps in the discussions - it can be achieved and in my Asset Management and Operational Leadership training courses I present several case studies of where it has been achieved in practice.

Best wishes, John Doran.

NIST addressed this a few years ago in a joint SMRP government relations project: Economics of Manufacturing Machinery Maintenance (link opens in new window) as part of the 'Manufacturing Machinery Maintenance' project (opens in new window).  They reviewed and tied corporate KPI to maintenance activities including maintenance costs, preventable losses, and benefits of advanced maintenance strategies.  They were also able to relate the following (from NIST web page):

Maintenance Costs: 2016 Machinery maintenance expenditures for NAICS 321-339 (excluding 324 and 325) were estimated to be $57.3 billion. Additional expenditures due to faults and failures were estimated at $16.3 billion and costs for inventory to buffer against maintenance issues costed $0.9 billion. In total, these maintenance activities costed $74.5 billion.

Preventable Losses: The 2016 losses due to preventable maintenance issues amounted to $119.1 billion: $18.1 billion due to downtime, $0.8 billion due to defects, and $100.2 billion due to lost sales from delays and defects. Additionally, an estimated 16.03 injuries and 0.05 deaths per million employees were associated with these maintenance issues.

Benefits of Advanced Maintenance Strategies: The estimated 2016 perceived benefit of adopting some additional amount of predictive maintenance was $6.5 billion from downtime reduction and $67.3 billion in increased sales ($73.8 billion in total). Other perceived benefits such as reduced defects are also likely to occur but were not monetized.

The top 25 % of those establishments relying on reactive maintenance was associated with 3.3 times more downtime than those in the bottom 25 %. They were also associated with 16.0 times more defects, 2.8 more lost sales due to defects from maintenance, 2.4 times more lost sales due to delays from maintenance, and 4.9 times more inventory increases due to maintenance issues. On average, 45.7 % of machinery maintenance was reactive maintenance. Those who relied less on reactive maintenance, and more on preventive and/or predictive maintenance, were more likely to use a pull (i.e., make to order) stock strategy and tend to be differentiators as opposed to being a cost competitor. That is, they rely more on their reputation and produce products on demand. The implication being that reactive maintenance reduces quality and increases uncertainty in production time.

Among those establishments that primarily rely on preventive and predictive maintenance (i.e., less than 50 % reactive maintenance), the top 50 % in predictive maintenance was associated with 15 % less downtime, an 87 % lower defect rate, and 66 % less inventory increases due to unplanned maintenance. Those establishments that relied more on predictive maintenance than preventive were more likely to have a pull (i.e., make to order) stock strategy and more likely to be a differentiator as opposed to being a cost competitor. Moreover, predictive maintenance is associated with higher quality products and shorter production times through reduced downtime. For those establishments that invested more heavily into preventive or predictive.

In addition, in tying our work on project implementation with our industry partners we tie energy and emissions (energy in general, emissions with companies that have ESG goals) to the activity.  These are measurable values and maintenance activities were identified by the US Department of Energy in the 1990s as the number one method for decreasing energy spend by a corporation.  Rutgers University energy extension center and the University of Illinois' Energy Resources Center identified a minimum energy reduction of 14% just through the application of a maintenance program from a reactive maintenance program.  This was later implemented at the National Institutes of Health CUP with a combined predictive/preventive condition-based program on boiler and chiller systems with a resulting impact of ~50% reduction in overall energy spend (electric, gas, water) and was also proven with the US DOE's commercial/industrial 'Save Energy Now' program that started in 2005-2010(ish).  The tools available for that program (developed starting in 1993-present) can be found: software tools, including MEASUR; Link to all other case studies, manuals, tools, etc.  The initial impact of the Save Energy Now program at General Motors in the area of steam and energy, for instance, can be found on P. 42 of the August 2006 edition of Uptime Magazine (link here in separate window).

Just some food for thought on this topic.

I so agree with this Vic. I started a process with a man at the Zurich University of Applied Sciences. He specialises in finding the links between different primary parameters and its money effects. We tried to find good links between the normal parameters found in maintenance, and the size of the budget. But it was difficult to get meaningful relationships. If there are anyone out there that has insights regarding this, I would love to take that process up again. 

I so agree with this Vic. I started a process with a man at the Zurich University of Applied Sciences. He specialises in finding the links between different primary parameters and its money effects. We tried to find good links between the normal parameters found in maintenance, and the size of the budget. But it was difficult to get meaningful relationships. If there are anyone out there that has insights regarding this, I would love to take that process up again.