Process
Today, transparency is crucial for effective collaboration among companies, customers, and suppliers, fostering shared visibility. Processes play a pivotal role in enhancing the quality of products and services, concurrently improving operational efficiency and effectiveness. This, in turn, enhances competitive positioning while minimizing costs and waste.
The synergy between systems and processes establishes vital connections among involved parties, refining supply chains and cost structures. The driving forces behind process improvement lie in enterprise visibility, analytics, and professional data management. We specialize in aligning the business model and data model to optimize company performance.
Alexicon offers services tailored for major system integrators and large enterprises aiming to harness the potential of business, digital capabilities, data and Lean Six Sigma (LSS).
Process Mapping
Process mapping is like creating a visual blueprint of how work flows through a system. Imagine each task or activity as a box, and the connections between them as lines showing the sequence of steps. When you drill down into a box, it's like zooming in to see the details of that specific task, which may involve multiple smaller steps or actions.
These lines not only show the sequence of tasks but can also indicate how long it takes for things to move from one step to another, both in terms of quantity (like products produced) and dollars (financial transactions). So, process mapping helps to not only understand the big picture of how work moves through a system but also the finer details of time and resources involved at each step.
Process Flowchart
Creating a flowchart of the manufacturing process is a common approach to visualize the As-Is environment. This flowchart helps identify connected and unconnected machines, as well as manual processes that may need to be integrated or optimized through analytics.
- Mapping the process: The flowchart outlines each step of the manufacturing process, including the machines, equipment, and manual tasks involved. This provides a comprehensive overview of how materials flow through the production line and how different components interact with each other.
- Identifying connections: By analyzing the flowchart, manufacturers can identify connections between machines and processes, as well as potential bottlenecks or areas of inefficiency. This helps prioritize areas for improvement and optimization.
- Integration opportunities: Some machines or processes may be disconnected from the main production line or operate independently. Analytics can help identify opportunities to integrate these disconnected elements into the overall workflow, improving efficiency and coordination.
- Manual intervention: In some cases, manual intervention may be necessary, either due to the complexity of the process or the limitations of existing technology. Analytics can help optimize manual tasks by providing insights into resource allocation, scheduling, and workflow management.
By using flowcharts and analytics together, manufacturers can gain a clear understanding of the As-Is of environment, identify opportunities for improvement, and develop a roadmap for digital transformation that maximizes efficiency and productivity across the manufacturing process.
Process Mapping Examples
Here are some examples of areas for process mapping in a manufacturing company that handles both continuous and discrete products across various functional areas:
Supply Chain Management:
- Supplier Management: Mapping the process of sourcing raw materials and components, including supplier selection, qualification, and procurement.
- Inventory Management: Mapping the flow of materials through the warehouse, including receiving, storage, and distribution to production lines.
- Demand Planning: Mapping the process of forecasting demand for both continuous and discrete products, including sales forecasting, production planning, and inventory replenishment.
Production Planning and Control:
- Production Scheduling: Mapping the process of creating production schedules for both continuous and discrete manufacturing processes, including batch scheduling, machine allocation, and resource optimization.
- Work Order Management: Mapping the process of issuing work orders for production tasks, tracking progress, and managing exceptions or changes.
- Quality Control: Mapping the process of monitoring and controlling product quality throughout the production process, including inspections, testing, and non-conformance management.
Manufacturing Execution Systems (MES):
- Shop Floor Operations: Mapping the process of executing production tasks on the shop floor, including machine setup, operation, and maintenance.
- Production Tracking: Mapping the process of tracking work-in-progress (WIP) and monitoring production performance in real-time, including production rates, downtime, and efficiency metrics.
- Work Instructions: Mapping the process of delivering standardized work instructions to operators on the shop floor, including process steps, safety guidelines, and quality standards.
Enterprise Resource Planning (ERP):
- Order Management: Mapping the process of managing customer orders from receipt to fulfillment, including order entry, order processing, and order fulfillment.
- Financial Management: Mapping the process of managing financial transactions and reporting, including accounts payable, accounts receivable, and general ledger.
- Human Resources: Mapping the process of managing workforce-related activities, including hiring, training, performance management, and payroll.
Product Lifecycle Management (PLM):
- Product Development: Mapping the process of developing new products or variants, including product design, engineering changes, and prototype testing.
- Document Management: Mapping the process of managing product-related documents and data throughout the product lifecycle, including specifications, drawings, and revisions.
- Change Management: Mapping the process of managing changes to product designs or configurations, including change requests, approvals, and implementation.
By mapping these processes across functional areas and integrating them with ERP, MES, and PLM systems, manufacturing companies can streamline operations, improve visibility, and optimize performance across the entire value chain.
Analytics helps manufacturers understand their current operations by analyzing data from various sources such as production lines, supply chain, and equipment sensors. This analysis provides insights into inefficiencies, production bottlenecks, quality issues, and resource utilization. By identifying areas for improvement, manufacturers can optimize their processes before implementing digital solutions.
- As-Is environment analysis: Analytics helps manufacturers understand their current operations by analyzing data from various sources such as production lines, supply chain, and equipment sensors. This analysis provides insights into inefficiencies, production bottlenecks, quality issues, and resource utilization. By identifying areas for improvement, manufacturers can optimize their processes before implementing digital solutions.
- During system implementation: Analytics guides manufacturers in implementing digital solutions by providing data-driven insights into the impact of changes on operations. For example, predictive analytics can forecast the effects of process modifications or equipment upgrades, helping manufacturers make informed decisions and mitigate risks during implementation.
- Post-implementation monitoring: After the digital system is implemented, analytics continue to play a crucial role in monitoring and optimizing operations. Manufacturers can use real-time data analytics to track key performance indicators (KPIs), detect anomalies, and identify opportunities for further improvement. This ongoing analysis ensures that the digital system operates efficiently and delivers the expected benefits over time.
Analytics guides manufacturers in implementing digital solutions by providing data-driven insights into the impact of changes on operations. For example, predictive analytics can forecast the effects of process modifications or equipment upgrades, helping manufacturers make informed decisions and mitigate risks during implementation.
Overall, analytics are essential in the manufacturing process for both understanding the current state (As-Is environment) and optimizing operations before and after implementing digital solutions, ensuring continuous improvement and competitiveness in the industry.
Business and Digital Data (Integrated)
Analytic tools and data need to align with both business and technical processes to enhance enterprise operations.
Lean Six Sigma (LSS)
LSS stands as the cornerstone of operational excellence, seamlessly integrating its effectiveness across factory and office landscapes. Originating in manufacturing, LSS has evolved into a cross-industry powerhouse, revolutionizing sectors including service-oriented offices, healthcare, and administrative processes.
In factories, LSS methodologies act as a catalyst, streamlining manufacturing processes, reducing waste, enhancing product quality, and improving overall efficiency. Transitioning to office environments, these principles optimize business processes, minimize errors, and elevate productivity. The overarching goal is to eliminate unnecessary steps, reduce variability, and strengthen operational effectiveness, regardless of industry nuances.
Crucially, LSS seamlessly complements key pillars of modern Enterprise Operations, including Process Management, Analytics, Data Management and Data Science. This strategic synergy ensures a holistic approach, enhancing our ability to make informed decisions, drive innovation, and maintain a competitive edge in the market.
Alexicion not only recognizes the significance of LSS but also employs a unique approach by incorporating insights from diverse systems and recent advancements in data science. Within the realm of business management, LSS finds a broader application, enhancing both process efficiency and analytical precision to achieve desired outcomes.
Embedded in the belief that exceptional products and services fuel customer delight and loyalty, our performance services at Alexicon reflect a management-oriented LSS approach. This involves streamlined processes and meticulous measurements, ensuring not just efficiency, but sustained profitability.
U.S. Department of Commerce - National Institute of Standards and Technology (NIST)
International Standards Organization (ISO)
ISO 9000 is a series of five international standards published in 1987 by the International Organization for Standardization (ISO), in Geneva, Switzerland. Companies use the standards to help determine what they need to maintain an efficient quality conformance system. For example, the standards describe the need for an effective quality system, regular calibration of measuring and testing equipment, and an adequate record-keeping system. ISO 9000 registration determines whether a company complies with its own quality system.
The standards define minimum requirements for quality assurance systems that directly influence product quality and customer satisfaction without suggesting tools for analysis, prioritization, and evaluation.
Six Sigma
The aim of Six Sigma is to reduce variation through statistical methods that lower process defect rates to less than 3.4 defects per million opportunities. Six Sigma focuses on putting measurement systems in place for work processes. Within these systems, Six Sigma projects identify the need to reduce variation and improve processes.
Six Sigma projects may involve anything from improving the processes involved in mass-producing component parts to completely redesigning an aircraft completion process so that the aircraft requires less maintenance. The Six Sigma methodology DMAIC (define, measure, analyze, improve, and control) is the system for improving existing processes that fall below specifications and need incremental improvement. DMADV (define, measure, analyze, design, and verify - sometimes referred to as Design for Six Sigma [DFSS]) - is used to develop new processes or products at Six-Sigma-quality levels.
Lean
Lean is a series of tools and techniques for managing your organization's processes. Specifically, Lean focuses on eliminating all non-value-added activities and waste from processes. Although Lean tools differ from application to application, the goal is always incremental and breakthrough improvement. Lean projects might focus on eliminating or reducing anything a final customer would not want to pay for:
- scrap
- rework
- inspection
- inventory
- queuing or wait time
- transportation of materials or products
- redundant motion
Lean-focused organizations extend the concepts of waste elimination and value-added processes to suppliers, partners, and customers. At full potential, all aspects of a Lean organization's value chain have eliminated waste and are operating at full value-added potential.
Enterprise. Orchestrated.