Chapter 1: The Legitimate of Carbon Dioxide CO2 Toxicity Level in the Atmosphere

The Legitimate of Carbon Dioxide CO2 Toxicity Level in the Atmosphere

This document covers the area of customer and supplier interaction, the legitimate carbon dioxide CO₂ trend in your organization that you should know. Applicable to high volume, repeated transaction environment – manufacturing based.  (It can also be applied to service industry.)

Perception of Carbon Dioxide CO₂ Level

This document discusses the legitimate figures of carbon dioxide level in the atmosphere specified as a guideline. Carbon dioxide gas, which is increasing, due to combustion of hydrocarbon/methane, for example – power station, car, aircraft, etc. in the world we live in today. Fuelling the economy, hydrocarbon/methane has endangered human beings and the risks that we are involved. These figures are at alarming limit/level in the world that we live in today – an increasing rate.

A general perception of carbon dioxide CO₂ level in confined space requirement, is as defined in figure 1, is certainly at an alarming situation. The increasing concentration of carbon dioxide in parts per million ppm limit in the air we inhale every moment is true. Below is a common guideline of ppm level relating to the atmospheric gases in the environment we live in today

Figure 1: Air Quality – Carbon Dioxide CO₂ Level ppm

Limit    ppm level        Scenarios

1          250-400           “Normal” background concentration in outdoor ambient air

2          400-1000         “Indoor” Concentration typical of occupied indoor space with ace
                                    with good air exchange

3          1000-2000       “Poor Air Quality Complaints of drowsiness

 

Generally, carbon dioxide CO₂ level in the atmosphere is increasing day-by-day. And this trend is observable at Mouna Loa Observatory. Looking forward to this recorded trend, human beings are at risk of low-quality air level in future undertakings due to this fact/trend.

Graph 1: CO₂ Atmospheric Level (ppm) – Past / Current Readings

Source : Trends in CO2 - NOAA Global Monitoring Laboratory – measurements collected from on top a clear mountain in Mauna Loa, Hawaii

As an example, it is said that it is used to be that we are living in an environment that is conductive to good health. Next it is said that we are always in an “indoor” situation, which we are today. Can this process be reverse?

Combustion of hydrocarbon/methane is an irreversible process, that the emission of carbon dioxide is harmful at alarming limits., and that we are now at “indoor” situation. This gas is toxic and lethal at high level, herein called the “possible cause of poor air quality”. This “unhealthy breathing circumstances” especially to those that required “normal/good air quality”. The question that probably everybody is asking is whether the concentration carbon dioxide CO₂ level is reducing or able to reduce to its original limits?

Graph 2: Projecting CO₂ Atmospheric Level (ppm) – The Future Prediction, With Formulae/Equations

Red Line: 600ppm horizontal limit
Blue Line: 370+(0.43*exp (0.27*(t+11) ) )
Green Line: { [370 + (0.43*exp(0.27*(t+11) ) ) ] -
                                [ (-10) + (0.37* -1 * exp ((t+1) *0.405)) ] -
                                 [ (-10) + (0.37* -1 * exp ((t-3) *0.405)) ]      }
(Note: Data as shown is indicated herein based on the established formulae/equations, with possible reduction to achieve the required result)
This is the finding and equations to support this notion, as above: -
The detail formulae/equations with graphs and tables are as depict in Addendum I.

ADDENDUM I

The Detail Formulae/Equations with graphs and tables as depicted, from Chapter 1.

Table 1 : Exponential Equation Q2 = 370+(0.43*exp (0.27*(t+11) ) )                                                                  

t              A            B            C            Q2        

1             370        0.43      0.27      380.9795004   

2             370        0.43      0.27      384.3827551   

3             370        0.43      0.27      388.8408979   

4             370        0.43      0.27      394.6809065   

5             370        0.43      0.27      402.3311102   

6             370        0.43      0.27      412.352605     

7             370        0.43      0.27      425.4804069   

8             370        0.43      0.27      442.6773608   

9             370        0.43      0.27      465.204759     

10          370        0.43      0.27      494.7148498   

11          370        0.43      0.27      533.3720197   

12          370        0.43      0.27      584.0115381   

13          370        0.43      0.27      650.3475069   

14          370        0.43      0.27      737.2452679   

15          370        0.43      0.27      851.0782456   

16          370        0.43      0.27      1000.1954        

17          370        0.43      0.27      1195.533571   

18          370        0.43      0.27      1451.419631   

19          370        0.43      0.27      1786.621272    

Table 2 : Exponential Equation Q4-1 = (-10) + (0.37* -1 * exp ( (t+1) *0.405) )                                                               
             : Exponential Equation Q4-2 = (-10) + (0.37 * -1 * exp ( (t-3) *0.405) )                      

t              A            B            C            Q4-1                 Q4-2    

1             -10         0.37      0.405    0                          0            

2             -10         0.37      0.405    0                          0            

3             -10         0.37      0.405    0                          0            

4             -10         0.37      0.405    0                          0            

5             -10         0.37      0.405    0                          0            

6             -10         0.37      0.405    0                          0            

7             -10         0.37      0.405    -19.44747705      0            

8             -10         0.37      0.405    -24.16462596      0            

9             -10         0.37      0.405    -31.23705911      0            

10          -10         0.37      0.405    -41.84077581       0            

11          -10         0.37      0.405    -57.73895478       -19.44747705  

12          -10         0.37      0.405    -81.57513425       -24.16462596 

13          -10         0.37      0.405    -117.3127777       -31.23705911 

14          -10         0.37      0.405    -170.8943159       -41.84077581 

15          -10         0.37      0.405    -251.2292501       -57.73895478 

16          -10         0.37      0.405    -371.6756178       -81.57513425 

17          -10         0.37      0.405    -552.261158         -117.3127777  

18          -10         0.37      0.405    -823.0135098       -170.8943159  

19          -10         0.37      0.405    -1228.953188       -251.2292501 

Note :   Q4-1  - Begin from t=7                                                                             

             Q4-2 - Begin from t=11

Table 3 : Sum of Exponential Equations Q2 + Q4-1 + Q4-2

t              Q2                        Q4-1             Q4-2                Q2+Q4-1+Q4-2

1             380.9795004    0                       0                      380.9795004

2             384.3827551    0                       0                      384.3827551

3             388.8408979    0                       0                      388.8408979

4             394.6809065    0                       0                      394.6809065

5             402.3311102    0                        0                      402.3311102

6             412.352605      0                       0                      412.352605

7             425.4804069    -19.44747705   0                      406.0329299

8             442.6773608    -24.16462596   0                      418.5127348

9             465.204759      -31.23705911   0                      433.9676999

10          494.7148498    -41.84077581    0                      452.874074

11          533.3720197    -57.73895478    -19.44747705  456.1855879

12          584.0115381    -81.57513425    -24.16462596   478.2717778

13          650.3475069    -117.3127777    -31.23705911   501.7976701

14          737.2452679    -170.8943159    -41.84077581  524.5101761

15          851.0782456    -251.2292501    -57.73895478  542.1100407

16          1000.1954        -371.6756178    -81.57513425  546.9446478

17          1195.533571    -552.261158       -117.3127777   525.9596351

18          1451.419631    -823.0135098    -170.8943159   457.5118048

19          1786.621272    -1228.953188     -251.2292501  306.4388344

ADDENDUM II

Machine Performance in Application for Modelling Trust with Random Number Generator to Predict Time Trends

 

The purpose of this paper is to show evidence of the plausible links that via random numbers approach; analysis of data trends is profitable in the manufacturing industry. Random numbers generated in EXCEL, for service delivery within the setup performance parameters, consisting of the summation of seven (7) valuable factored variables (producing a total overall point(s) in each delivery), can trend positively in a foreseeable future direction.

The analogy of “profitable trending transactions” and “reliable data trends”, is of similar ideas when comparing the same data in the past, applicable within the current situation(s) faced by many manufacturers. It is true when the outcome is the same for the two possible situations (1) dependent occurrence to depict foreseeable trends (that figuratively produce an indicate value) utilizing forecasting (or predicting) technique(s), and (2) the results of a parallel paradox presumably by splitting the current situations into two (2) segments in this world will show the same result(s) in the parallel realities.

Random numbers are generated uniquely. Individual numbers generated never repeats. When the series of numbers generated are sorted, it is in sequence - maybe an incremental linear trendline (i.e. lawful within a systemic order). It can be narrated in a perceptive, that it is behaving in a natural order, as well as in practice, which represents the real world we live in today.

Analysis and findings are reported herein based on probability of a count of chance in the respective quadrants, with the most probable in Category 2: positive incremental value amongst two past data, trust level between 50 to 80 within this category, with an overall point of about 54% on average herein. In addition, Categorization of Trust Level by Limits (considering the data within the governing limits, “between lower and upper limit” – mean area), the average value is about 53% to 62%.  Finally, the Moving Average technique, within a defined window of view, shows tremendous improvement in the average point, which is about 64% to 69%.
 
The Leadership of Manufacturer Active Paradigm (MAP) and/or Customer Active Paradigm (CAP) - The Factors that Influence Decision in Manufacturing

Management practices/techniques address manufacturing service issues. Probably we are now a Customer Active Paradigm (CAP) from previous practice of Manufacturer Active Paradigm (MAP); that is the goods and services, including the processes are designed to meet end customer satisfaction instead of customers accepting manufacturers’ products or services capabilities. In term of operational matters, improvements in products and services quality, increase in process flexibility, dependability of a plant, cost reduction and reduction in the time to response (speed) to changes have overall been addressed to satisfy customers’ needs. These on-going operational strategies are summarized, with the aims reasoned as follows: -
 Flexibility improvement – more products/services variety, meeting end customer satisfaction required in todays’ environment to remain competitive with a single process/procedure,
 Cost reduction – waste elimination and reject reduction,
 Quality Improvement – promising more sales due to less defects, i.e. statistical count based on probability built-in process line to detect/diagnose the fault(s) before it occurs,
 Dependability – efficient plant that customers can rely on its output(s),
 Speed – shorter lead time, improving time to respond to change in customers’ appetite.
With these strategies in place, it promises an increase in sales figures, claiming profit increase as required annually. Considering some current trends in practice, are the objectives achieved?

Engineering contribution in this case is automating the processes and has become common as it shows evidence that it is in support of these strategies. With the process technology available today, it has emerged to manage the parameters effectively.
·       A flexible system, for example in a flexible manufacturing system (e.g. CNC machines), allows flexibility in terms of products/service variety, enables more reactive to changes in customer appetite/design.
·       Cost reduction - The use of computer simulation to optimize the processes is a move to reduce the risk level before implementing the solution.
·       Quality Improvement- Also with diagnostics feature that allows on-line quality checks, which are built into the process lines, assures production situation in real circumstances.
·       Reliability (dependable) system, for instance, a Safety Instrumented System SIS with its initiators (sensors/detectors) and actuators has remarkable PID Controllers to effectively manage the flow process, as well as its functional logic program to protection on demand, safeguarding the plant asset, personnel and the environment.
·       Time to react to customer change (speed) - De-bottlenecking project in manufacturing facilities identifies the critical tasks and thus eliminates it through innovative solutions.
Depending on the type of application, these engineering solutions have managed to serve the function in a continuous improvement environment. Business nature is always looking for an upgrade of its facilities to be a “world class” player to prepare to serve future demand. Costly project investments must register foreseeable returns before they move forward.
 
The Current Change That Enables Mass Production to Batch Processes, A Variety Matter

The change in production output figures has changed for some organizations but not all. This has changed from mass/continuous to batch production, with the conditions that it meets the required demand or some degree of variety out of a single process. In mass production, the stock level is high and the variety of choices to end customer is limited. However, in batch production, it is.

Let us examine the processes in a system to transform raw materials to finish goods or services by their nature and the determined purpose. In every of these processes, the critical path of a particular system of interest is regarded as the backbone of the project where any conventional practices or approaches along this path are changed to either fully or semi-automated system, as the purpose outlined the benefits.

Raw materials are processed using the available technology, filled appropriately, shipped readily in batches. The capability of the processes caters for large quantities, but the drive for smaller batches (the demand) claims to reduce stock level at the next tier in the chain of supply. Thus, these efforts of management practices effectively contribute towards increasing money value to an organization and indirectly to the nation and region as a whole.

The operational costs have increased and have yet to increase even more year by year. Sales figures/volumes depend on demand, and pricing does come with competition. The inclusion of these strategies promises increasing profit, by examining the situation of increased flexibility in manufacturing products/services variety, dependable Safety Instrumented System SIS in processing facilities, frequent machine setups to reduce stock level, etc. as positive scenario of the situation.

Focus On Customers

Engineering management practices nowadays focus on customers. It must meet and/or exceed market requirements to remain competitive in the business environment today. A thought that will challenge our plant/process capabilities; strategizing work functions, organizing resources, etc. to meet and be ready for future uprising demand of the nation and also in the region.

In addition to the increase in technological costs (getting common nowadays) to achieve the promised results, staying ahead of business and remaining in good faith with the current business nature is the challenge in today’s business world.

 

Reviewing The Impact on Operations Management by The Latest Engineering Management Practices That Focuses on Customers

In today’s competitive environment, managing and operating a business in a profitable manner is important for organization sustainability, and to effectively increase profit yearly is a challenge. The methodology for increasing organizational profit has always been clear, focusing on customers. With the fact that the value for expensive goods/services is always decreasing every year due to inflation, management practices that focus on customers always ensure that internal factors contributed as cost adders are investigated and to add value in the supply chain.

Has the objective of adding value to the supply chain been achieved? Currently many organizations adopt well-known management practices to remain competitively ahead in their business. What are the underlining trends for good management practice that companies adopt to ensure success? The following are well-known management practices that focus on customers.

A few well-known and current management practices address waste elimination, stock reduction, continuous quality improvement, quality assurance, defect reduction and increase plant efficiency. These are a few engineering management practices that are adopted to add value to the organization.

 

1.1  Lean Management Practices – Waste elimination

Lean manufacturing system identifies and eliminates waste within the process. Single-minute exchange of die SMED, one of the many methods of waste reduction, provides a rapid and efficient way to reduce lot size (or stock up) by frequent setups/start-ups. Frequent setup of a single process offers greater product variety to customers.

 

1.2  Just-In-Time JIT, Management – Reduce Stock Level and Response Time to Change

To perform batch operation with low stock-ups, 5s practices developed in Japan identified as one of the techniques to enable Just-In-Time manufacturing, encourages reduction in stock level and improvement in cyclical response time. This technique, or Toyota Production System, sorts of things, set in order, shine to keep workplace clean, standardize the tasks and sustain the situation. Thus, philosophy adds value to the entire chain, meeting the needs to response to changing end customer satisfaction.

 

1.3  Total Quality Management – Continuously Improving Quality to Satisfy End Customer

It is a holistic approach for an organization that seeks continuous improvement in its ability to deliver high quality products and services to end customers. Quality control tools developed in the process are utilized, including inspection and diagnostics ability, to promise quality processes built into production system.

 

1.4  ISO 9000 / ISO 9001 – Quality Management System assuring product or service quality delivery

It is a standard that provides guidance to organizations who want to ensure that their products and services consistently meet the customer’s requirements, and that quality is consistently improved. As a quality management system, it is governed by procedures and quality manuals to achieve the goal.

 

1.5  Sigma Six – Reduces Reject Tremendously

A set of statistical tools and techniques to improve the process introduced in Motorola. With this, the main objective is to reduce defective products claiming only 3.4 defects in a million. It evaluates the manufacturing capability in delivery, meeting the specification requirements in the production of goods and services. This will ensure that customers do not own defective products/services.

 

1.6  Total Productive Maintenance – Higher Productivity through Maintenance of Equipment

It aims to increase plant and machinery equipment productivity by investing in maintenance. The focus is on working conditions to avoid breakdowns and delays in manufacturing processes. It is seen by its customers as a way of achieving higher efficiency.

ADDENDUM III

Bridging the ‘Error’ Gap

The architectural drawing of each typical design is a typical one, depending on the demand the size can be adjusted, i.e. the required quantities of Delay D Flip Flop is in question – a subjective congregate to a single matter of fact for gains in the control system.

A bridge in this situation is the physical layer in the digital architecture circuitry of a computer (system) whereby at data level, the data (real world) is received for processing. It is very important to note that any serial data that passes this internal circuit - modelled to perform the required task/job to ensure data transmission at this level.

The ‘error’ gap is determined by or controlled by a parity bit – either it is an even (0) or an odd (1) number, generates with an Even Parity Generator. The Even (0) or Odd (1) number must be calculated to ensure that data are transmitted properly between and within the transmitter and the receiver device.

Recommendation Standard 232 (RS-232)

Communication Protocol is a digital serial (interface) communication or known as serial data transmission that can transfer serial data between two (2) systems without any ‘error’. This means that data transmission is secure between two parties herein, call the transmitter and the receiver device. It is a two (2) way communication channel, enabling data to be transfer within the boundary limit(s) between both the parties.