Version Control (Git)

Understanding version control concepts:

Why Version Control:

History Tracking:
- Every change recorded
- Who changed what when
- Ability to review history
- Understand evolution

Collaboration:
- Multiple developers
- Coordinate changes
- Merge contributions
- Avoid conflicts

Safety:
- Rollback capability
- Experiment safely
- Recover from mistakes
- Backup implicit

Compliance:
- Audit trail
- Regulatory requirements
- Change documentation
- Traceability

Core Concepts:

Repository:
- Storage for project files
- Complete history
- Central or distributed
- Clone/fork copies

Commit:
- Snapshot of changes
- Descriptive message
- Atomic unit of change
- Unique identifier

Branch:
- Parallel development line
- Isolate changes
- Feature development
- Release management

Merge:
- Combine branches
- Integrate changes
- Resolve conflicts
- Unite work

Version Control Types:

Centralized (CVCS):
- Single central repository
- Subversion (SVN)
- TFS/Azure DevOps
- Simple model

Distributed (DVCS):
- Full repository copies
- Git (dominant)
- Work offline
- Flexible workflows

Git Overview:

Dominance:
- Industry standard
- Open source
- Massive ecosystem
- Platform independent

Key Commands:
- clone, pull, push
- add, commit
- branch, checkout
- merge, rebase

Platforms:
- GitHub
- GitLab
- Azure DevOps
- Bitbucket

Applying version control to manufacturing systems:

Automation Code Types:

PLC Programs:
- Ladder logic, structured text
- Project files
- Configuration
- Often binary formats

HMI/SCADA:
- Screen definitions
- Tag configurations
- Scripts
- Graphics files

Robot Programs:
- Motion programs
- Configuration
- Tool definitions
- Safety settings

Device Configuration:
- VFD parameters
- Network configuration
- Recipe data
- Calibration data

Challenges:

Binary Files:
- Many automation tools use binary formats
- Cannot diff effectively
- Large file sizes
- Export to text when possible

Vendor Diversity:
- Many platforms
- Different file formats
- Various export options
- Standardization difficult

Deployment:
- Download to equipment
- Configuration management
- Testing requirements
- Rollback procedures

Solutions:

Text Export:
- Export source code to text
- Track text versions
- Some loss of metadata
- Better than nothing

Vendor Solutions:
- Rockwell AssetCentre
- Siemens TIA Portal integration
- Version tracking built-in
- Limited Git integration

Best Practices:

Project Structure:
- Organize by system/machine
- Consistent naming
- Include documentation
- Configuration management

Commit Practices:
- Meaningful messages
- Atomic commits
- Reference work orders
- Include purpose

Branching Strategy:
- Main branch = production
- Feature branches for development
- Release branches
- Tagging for versions

Documentation:
- Change descriptions
- Testing notes
- Rollback procedures
- Dependencies

Establishing version control for automation:

Getting Started:

Tool Selection:
- Git for general use
- Consider vendor tools for integration
- Cloud vs. self-hosted
- Team familiarity

Repository Setup:
- Organize by project/system
- Access control
- Backup strategy
- Integration with other tools

Process Definition:
- When to commit
- How to branch
- Review requirements
- Deployment procedures

Workflow Models:

Feature Branch Workflow:
1. Create branch for change
2. Make and test changes
3. Code review
4. Merge to main
5. Deploy

GitFlow:
- Main branch: production
- Develop branch: integration
- Feature branches: individual work
- Release branches: preparation
- Hotfix branches: emergency fixes

Trunk-Based:
- Frequent small commits
- Short-lived branches
- Continuous integration
- Faster feedback

Code Review:

Benefits:
- Catch errors
- Knowledge sharing
- Quality improvement
- Documentation

Practice:
- Pull/merge requests
- Peer review
- Checklists
- Approval process

Integration:

With Project Management:
- Link commits to work items
- Traceability
- Azure DevOps, Jira
- Automated tracking

With CI/CD:
- Automated testing
- Build validation
- Deployment automation
- Quality gates

With Compliance:
- Electronic signatures
- Audit trails
- Change records
- Regulatory requirements

Version control skills in manufacturing careers:

Why It Matters:

Automation Engineer:
Modern automation requires:
- Code management
- Collaboration
- Change tracking
- Quality practices

Career Differentiator:
- Shows software engineering maturity
- Demonstrates best practices
- Enables modern workflows
- Valued by employers

Skill Levels:

Basic:
- Understand concepts
- Use existing repositories
- Basic operations
- Follow established procedures

Intermediate:
- Configure repositories
- Branching and merging
- Resolve conflicts
- Define workflows

Advanced:
- Architecture and strategy
- CI/CD integration
- Tool customization
- Process optimization

Learning Path:

Start with Git:
- Free and ubiquitous
- Abundant learning resources
- Practice with personal projects
- Online tutorials

Resources:
- Pro Git book (free online)
- GitHub Learning Lab
- Interactive tutorials
- Practice projects

Progress:
1. Basic commands
2. Branching and merging
3. Collaboration workflows
4. Integration with tools
5. Strategy and architecture

Career Impact:

Controls Engineer:
Version control enables:
- Professional code management
- Team collaboration
- Quality improvement
- Compliance support
$75,000-$110,000

Software/DevOps for Manufacturing:
Specialized role:
- Automation DevOps
- CI/CD implementation
- Process improvement
- $85,000-$130,000

Industries:
All automated manufacturing benefits:
- Regulatory (pharma, medical)
- High-complexity (automotive, aerospace)
- Distributed teams
- Modern automation practices

Version control is foundational for modern automation development.