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10 impacts to manufacturing metrics

Expectations from reading this article;

·         Understand some significant trends occurring and their impact to manufacturing.

·         Propose new considerations within metrics (see my final action hit list at the bottom of this article)

  • Provide some search hash tags for additional search by the reader

The internet of things #IOT Trend 1:

There is every clear signal that continued connectivity of devices will provide new opportunity for those capable of reading the information. With an estimated increase of devices online exceeding actual human users of the internet, one can rapidly understand its scale.

IOT (Internet of Things) in Manufacturing:

  1. New business models can be created with the use of IOT. Obvious areas are service, maintenance and R&D from product use.
  2. Collaboration of manufacturing centers will allow potential subcontract of machinery to help optimize productivity and lead times.
  3. Incremental improvements of product and design may become unacceptable for a fast changing market.
  4. Will the 80/20 rule be reversed where 80% of profit comes from 20% of products and customers?
  5. New platform and ecosystem thinking for products instead of features and benefits.
#Mfg metric thoughts: IOT will help create more metrics to define more accurate KPI’s for a business, uptime, and efficiency inclusing not least remote monitoring of out of ecosystem items
— James Doyle - JAMSO

Big data #bigdata Trend 2:

Many years ago companies kept paper files and records. Sometimes these had been indexed for ease of recollection and often not. The same can be said in many regards to the history of computer data. This picture is changing rapidly as cloud based storage becomes ever more speedy, reliable, secure and cost efficient.

Big data represents how to store and manage all this data. With the advancements in data heavy media such as video and audio plus the increasing number of people and devices online it is clear to see the need to manage and make use of all this data is a significant area of interest.

#Bigdata in manufacturing:

If engineers and scientists want one thing more, it is often data!

  1. We have left the industrial age and entered the information age, yet we just might see the return of industry riding on the back of new insights through the vehicle of big data.

  2. Process improvements from a wider data collection source can help reduce costs and improve efficiency for a business.

  3. Feedback information on quality from “in the field” products can shape the current processing and design methods of products in production.

  4. Improved risk calculations may create new design opportunities through enhanced design simulations, customer feedback and in use stress data from aging products

  5. Supply chain information will generate leaner and more accurate opportunity to retain quality, price, delivery improvements.

#Mfg metrics thoughts: New relevant metrics may be discovered as holding more value than current methods. Larger data sets and improved analysis will create more metric choice.
— James Doyle - JAMSO

Predictive analytics/machine learning Trend 3:

This video introduces Predictive Analytics to the absolute beginner. - created at http://goanimate.com/

The process to extract relevant information from available data sources and sets to identify patterns and forecast trends or outcomes. The improvements of this technology still are in its infancy within the public domain. Machine learning takes the predictive analytics results and compares to observed actual results. From this process the algorithm is improved and adjusted to improve future predictions.

Predictive analytics and machine learning in manufacturing:

  • Effective predictive analytics offers many opportunities in the areas of cost and price models, quality and reliability, supply chain management flow and maintenance or service. Predictive analytics is already a strong part of manufacturing and is set to continue making its impact.
  • The machine learning aspect however is in its infancy. Manufacturing process improvement is an ideal candidate area for expansion of the machine learning ( #ML #machinelearning ) and its brother “deep learning” for highly sophisticated complex actions and considerations, i.e. sorting animal stock for multiple variables in a changing environment that effects the animals or similar adjustments for machine tool processes.
Manufacturing metric considerations: The biggest area of metric development is between action and no action based on the predictive analytics information and machine learning proposed steps. This will aim performance, relevance and focus for improved efficiency.
— James Doyle - Founder JAMSO

Data Visualization #Dataviz Trend 4

The consumption of data has grown over time where the consumers have grown disengaged with many traditional methods of sharing information, for example bar charts or pie charts. With the emergence of new data sets and improved capabilities to process ever more complex data the methods of communicating it has opened with data visualization techniques. The principle aim is simple, to share in a visual context certain correlations or patterns that may be missed through text representation.

Data visualization in manufacturing.

Many extensive and broad use of data visualization in manufacturing are specific task related i.e. product assembly, heat transfer of materials. The future impact offers many exciting new insights.

  1. Correlations of multiple reliant process quality
  2. Improved supply chain information to strike the correct balance between scarcity and loss of sale whilst retaining optimal price and customer satisfaction
  3. Improved engagement of lower skilled staff with higher complex information sets
  4. Easier methods of communicating with wider customer data sets
  5. Modelling of new processes and increased variable options for design optimization.
Manufacturing metric considerations: New insights from previously discounted data and higher engaged staff.
— James Doyle - Founder of JAMSO

Artificial intelligence (AI) #AI Trend 5

Source :  singularityu.org

AI aims to seek reasoning through machine learning, knowledge, robotics, language processing and the planning of tasks.

AI in manufacturing:

Manufacturing will benefit from the production of robotic devices to fulfill the AI ambitions. To-date, robots are mostly used in dedicated cell areas and perform repetitive tasks. The future can be very different.

  1. Intelligent personal household robots, anticipating demands around the house at peak times of the day.
  2. Personal carers for less able bodied people such as elderly, sick and handicapped.
  3. Intelligent drones taking social roles within community.
  4. Intelligent factories capable of moving their production flow and machine placements depending on the product and quantity of products ordered.
  5. Hazardous and dangerous work environments become the domain of autonomous AI devices
Considerations for metrics in manufacturing using AI: Human morals and ethics to be agreed within strict performance criteria of the individual parts, sub systems and full interacting systems of the AI and AI/human ecosystem.
— James Doyle - Founder of JAMSO

Gamification #Gamification Trend 6

The continued rise of gamification in modern society is of special key interest. The concept of using themes and rewards as motivation to behaviors has a key role in education, social and business environments. See my prior articles on gamification: 

Gamification in performance management

Gamification in manufacturing:

The most common global use of gamification is within learning and education; this provides some specific benefits for production companies.

  1. Skills development to help deploy wider skill based workers with higher mastery of technical requirements.
  2. Team work and unified purpose can be generated to help cross shift workers and part time seasonal staff retain common goals and objectives for the business.
  3. Productivity levels can be improved where by focus on best practice takes over a prior focus on solving problems.
  4. Works well for connecting the whole supply chain with customers and across multiple site locations.
Metric considerations for gamification within manufacturing: The over use of standard histogram in business meetings contributes to low employee engagement. The use of appropriate gamification of the measures will encourage higher performance and deeper engagement.
— James Doyle - Founder of JAMSO

Customer Experience (#CE) / User Experience (UX) (#UX) Trend 7

 

The globalization of commerce in B2B and B2C environments means ever higher levels of improved customer service expectations. This includes the full range and time of a person's emotions and attitudes about using a particular product, system or service.

User experience in manufacturing.

  1. Imagine a technical customer support service that understands your level of skills in a specific and so provides faster the appropriate level of details you need to solve your issue.

  2. Adaptable design for left, right handed people and an aging population .

  3. Creating a product ownership process that highlights service elements that are more desirable than just the fit, form and function of a product.

  4. Changing and flexible interaction points of a physical product.

  5. Address sustainability of a full product life cycle.

Metric considerations for user experience: There are many individual subjective areas of measure that will need to be grouped for statistical relevance. A clear priority of the business / market / consumer needs will help identify KPI vs metrics
— James Doyle - Founder of JAMSO

Block chain (#blockchain) Trend 8

The technology behind the infamous Bitcoin and many other crypto-currencies is called the block chain. This technology is a significant revolution that has impacts way beyond finance. The ability of the block chain to become an open ledger is simple, pure and highly powerful for future society.

Block chain in manufacturing.

There is considerable under development and investment in this area as of 2015.

  1. The supply chain world is an ideal candidate to follow full trace of material source to consumer delivery.
  2. Device calibration and control using block chain technology will open. new product process potential.
  3. Regulatory control is easier for many high risk candidate process’s.
  4. Linking of consumer specifications to delivered product control.
  5. Potential impact to reinvent ERP systems.
Metrics considerations with block chain: Real time metrics are more challenged within this technology however there are more upsides than downsides!
— James Doyle - Founder of JAMSO

Cyber security #cybersecurity Trend 9

The revelations by Edward Snowden had a profound impact across the globe; we also see continued escalation and increase of hacking activity. The developed world has become as dependent upon technology and data as it has become on water. This is a bold statement to make but consider your water and electric supply could/would be seriously affected through loss of data to manage and supply it.

The need to protect control and ownership of data includes from privacy, IP and physical control of our lives and touch-points. The future risks of cyber crime extend beyond our current levels of understanding and knowledge.

Cyber security in manufacturing.

Clearly risk of hacking and system error will increase in importance as more devices become connected online.

  1. Low value products will require high level cyber security levels to reduce back door entry to manufacturing systems.
  2. Intellectual property (IP) will continue to be a battle ground area, strict policy and access procedures to individuals and parts of the full data system will need new solutions (big data+block chain?)
  3. Safe default settings to be applied for system outages
  4. Open source vs closed source technology will be a debate for many years to come for their unique benefits for improved cybersecurity yet a combination may become the optimum solution.
  5. Improved policy development to turn into new standards for designed in security across service/products
Metrics considerations for manufacturing in cyber security: Levels of know how, policy, procedures and strategy updates.
— James Doyle - Founder of JAMSO

3D Printing #3DPrinting Trend 10

Source : Avi Reichental, CEO of 3D Systems, presents "3D Printing 101", a quick 4 min introduction to the field of 3D printing.

3D printing is in its infancy and yet offers many dynamic flexible options to produce goods.

3D printing in manufacturing.

  1. New materials can be created with different levels of density and properties, this opens the door to design concepts not seen to date
  2. Local production for small/medium volume production offer opportunity for personalization of product design
  3. Large companies may become more software technology companies as their designs are then produced via localised 3D printers.
  4. Smaller products and the creation of new markets with small nano sized products impact every industry.
  5. 4D products is an idea where the form and shape of a product changes due to other variables i.e. Pressure, temperature, dryness
Metric considerations for 3D printing in manufacturing: Most current production related metrics will remain; a key development will be to measure remote quality when branded products are produced remotely plus the supply chain costs to define when critical mass occurs to remove local production to mass production.
— James Doyle - Founder of JAMSO

New trend impacts to metrics and KPI's in Manufacturing

The metrics and performance indicators applicable many decades ago have evolved with improved technology and new demands; this is clearly the case as we have explored each of the new trends within manufacturing.

The ultimate design purpose of metrics and KPI’s remain the same. They should be to help the business perform to desired levels and allow correct information for actions to be taken.

Too many metrics may have been a challenge for many managers over the past 20 years and yet we now enter a period of time where data collection can utilize the power of big data, machine learning and artificial intelligence to identify and communicate through use of data visualization new synergies not previously manageable, known or capitalised upon.

There are some metrics these new trends highlight as key areas of interest:

1)      Improvements in customer and user experiences in real time.

2)      Governance and compliance areas for security

3)      Supply chain quality (Mobile, plastics, bandwidth, screen sizes)

4)      Capacity utilization of computer power, information band width and processing power

5)      Uptime will remain a critical measure in an online world

6)      Rate of change from concept to market implementation

7)      Energy cost per transaction

8)      Productivity levels of employees and computer equipment

9)      Revenue growth

10)   Cost of customer acquisition

11)   User and customer churn rate

12)   Contribution margin for specific product/service lines

13)   Future technology investment costs

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