Future of Manufacturing

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Based on McKinsey survey done on more than 1000 companies following are some key points to note: 

• Lack of resources/knowledge to scale
• Lack of data analytics skills in-house
• Lack of interest in Innovation
• High cost of scaling
• Hard to justify business case without short-term impact
• Pilots demonstrate unclear business value 
• Lack of trust in scalability of platforms
• Risks to data security
• Unclear Budget Value
• Lack of leadership support and attention
• Too many stakeholders and with different concept
• Less support from some field employees due to job insecurity
• Country’s Political situations & Policies

• Secure CEO support 

• Work together with management to develop an ROI roadmap and allocate IT

  and OT resources accordingly. 

• Set the vision and the value to capture

• Consider focusing on smaller companies. The bigger companies tend to be

  more difficult due to the sheer number of stakeholders

• Focus on quick-wins which can always build the momentum necessary to drive

  digital transformation. 

• Promote these small-scale wins across the company to inspire employees

• Build skill & capabilities in your team

• Scaling up will be easy if pain points are seen solved during pilot 

• Clearly define roles & responsibilities

• Redefine customer/user experience

• Set clear, ambitious targets based on cost savings, revenues, improved

  performance 

• Build the Skills empower a dedicated team to lead the charge. 

• Nurture a digital culture

• Treat data as a transformational asset for business model

• Adopt a new operating model

• Appoint a high-caliber launch team led by a chief digital officer/CTO

• Initiate the Cultural of Innovation in the company. 

• Avoid using Buzzwords…

• Automation of machines and Production Lines

• Process Integration with cloud based ERP, MES, CRM and PLM software

  applications

• Systems and IT-OT Networks must be Cyber secured 

• Use of glasses in Augmented Reality to receive only relevant data from the

  production  floor

• If needed then use Robots/Cobots to automate challenging tasks

• Reduce Losses (Down Time, Changeover, Performance Loss, Quality Loss)

• Reduce the Downtime

• OEE increase

• Productivity increase

• Cycle time can be optimized through Big Data analytics

• Process Optimization ( Use comparison tools to see where to focus attention,

  Use trend tools to see which KPIs are improving and which are getting worse)

• Cloud-based analytics for predictive maintenance & Preventive Maintenance to

  save time and money

• Energy monitoring and manage the power consumptions

• Increase speed to deliver the product to customer