When it comes to bringing AM into production, companies struggle to manage the resources at their disposal that lead to growth, but also profitability. This is due to a lack of process knowledge, high upfront costs in AM, as well as a lack of transparency in terms of efficiency and profitability. As a result, decisions on the next growth steps are made on an ad-hoc basis based on the most pressing issues at hand as well as reactionary moves because of operational challenges or customer requests.
To help manufacturers bring this technology into production in a sustainable, but most importantly a profitable way, we propose metrics to help make decisions on the next strategic investment and growth approach. For this, we first introduce an AM-specific modified version of OEE and DuPont analysis, which connects profitability and ROI to a direct analysis of production efficiency. Next, we introduce the management of other critical production resources: powder as well as people. Finally, we walk through the KPIs and decision gates that need to be defined to ensure that the profitability of the business is growing along with the investments that the company needs to make. To that extent, we will describe three phases of growth: initial start of operations, scaling, and 'serial production.' What we mean by serial production are stable orders of a specific application, be that 10 parts per year or 50,000 parts per year.
With these tools, we will demonstrate how operations and efficiency on the shop floor directly impact profitability as well as the decisions that the organization makes towards their growth strategy.
Consequently, we will discuss when users should acquire new systems, more power and hire new people to expand their operations profitably at all stages of growth.
Learning Objectives:
- Analyze their production from an efficiency and profitability perspective just like any other manufacturing technologies.
- Deliver cheaper parts to their end-users and minimize their production costs, thus accelerating the growth of their businesses.
- Make decisions on when to acquire new systems, hire new people or any other investment decisions that they will make based on data-driven KPIs rather than gut-feelings.
