## Introduction

You have received an introduction to manufacturing analytics, and now you will learn about process maps. Process maps in manufacturing visually represent the steps involved in producing goods, providing a clear understanding of workflows and identifying areas for improvement. They help teams see the entire process from start to finish, highlighting inefficiencies and bottlenecks. There are two main types of process maps: current state and future state. The current state process map depicts the existing workflow, showcasing the actual process and its issues. In contrast, the future state process map outlines an improved workflow, illustrating the desired process after implementing changes. These maps are essential tools for continuous improvement and lean manufacturing initiatives.

## Objectives

- Define current and future state process maps.
- Define bottlenecks and standard cycle time.

## Manufacturing Perspective

Current state process maps in manufacturing depict the existing workflow, highlighting all the steps, activities, and interactions involved in producing a product or delivering a service. These maps provide a comprehensive view of the current operations, including any inefficiencies or bottlenecks.

Current State Process Map

A current state process map depicts the existing workflow from beginning to end.

In contrast, future state process maps represent the desired state of the manufacturing process after improvements or optimization initiatives have been implemented. They outline the ideal workflow, incorporating changes to address inefficiencies identified in the current state. Future state process maps serve as a roadmap for achieving operational excellence and realizing strategic objectives in manufacturing.

Future State Process Map

A future state process map illustrates the desired workflow after implementing improvements to enhance efficiency.

Data analytics informs future state process maps by providing insights into current operations. Analyzing data helps identify inefficiencies, optimize workflows, and predict outcomes. By integrating data-driven insights, future state process maps can reflect the ideal state of operations, leading to improved efficiency, quality, and productivity in manufacturing.

Bottlenecks in current state process maps are points where workflow slows down or gets stuck, reducing overall efficiency. Identifying these bottlenecks is crucial as they highlight areas needing improvement. From a production planning standpoint, the slowest bottleneck is the fastest the plant can operate when production rates are normalized between production equipment. In future state process maps, these bottlenecks are addressed and eliminated through process redesign and optimization. By comparing current and future state maps, teams can visualize the impact of changes, ensuring a smoother, more efficient workflow. Addressing bottlenecks helps streamline operations, reduce lead times, and improve overall productivity in manufacturing.

Bottleneck

Bottlenecks in manufacturing are points where production slows, hindering overall efficiency.

Standard cycle time in manufacturing is the predetermined amount of time required to complete one cycle of a specific process or operation under normal working conditions. It is established through time studies that average the duration of multiple observations, considering factors like task complexity, worker skill, and equipment quality. This metric is essential for efficient production planning, scheduling, and resource management. Adhering to standard cycle times helps maintain consistent product quality, optimize productivity, and identify areas for improvement. It is a key element in lean manufacturing and continuous improvement efforts, promoting operational efficiency and cost-effectiveness. It can be calculated by standardizing across each process step, for example units per minute (units/minute) or pounds per hour (lbs/hour).

Standard Cycle Time

Standard cycle time is the established time to complete one production cycle under normal conditions.