Part 1 of a 2 Part Series
By Martin van der Roest
Introduction – A Perfect Storm for Uncertainty
Automotive suppliers face a combination of market forces that have created a unique business environment – an environment where uncertainty and unmitigated risk are eroding profit margins. Why are other manufacturing models immune and what’s so different about automotive suppliers? High volume production combined with product complexity create a perfect storm for uncertainty and risk. This article deconstructs these risk factors and explores strategies and tools to calm the storm.
Let’s take a closer look. There are external forces that can’t be controlled such as macro-economic pressures, regulations, cost pressures and intense competition. These forces are contrasted by internal factors that can be controlled. These include improving productivity, zero defect production and reducing risks. All the while, the daily battle cry is to achieve the quoted profit margins.
The term “Business of Engineering,” was coined by Aras’ CEO Peter Schroer, and is used to suggest that product lifecycle management (PLM) is no longer confined to the engineering realm. Rather, PLM is part of an enterprise-wide strategy and represents the fundamental ingredients to achieve the promises of a digital transformation.
Given the challenges that automotive suppliers face and the advancements of PLM and supporting technologies, there’s no better time for suppliers to consider the business of engineering offered via PLM.
This article is the first of a two-part series. Part 1 explores the key elements that obstruct productivity and erode profits. This includes data disparity, the lack of process repeatability and poor decision making visibility. In Part 2, the enabling role of PLM’s operational capabilities is examined and mapped into the various lifecycle activities as dictated by the industry’s overarching Advanced Product Quality Planning (APQP) process.
It all starts with the Quote
The quotation offered by an automotive supplier represents a significant collective effort of the organization. The pricing needs to be competitive, and the margins need to be achievable … and sustainable over the term of the program.
Said another way, the nature of production can amplify the risk inherent in the complexity of the order. For automotive suppliers, these risks represent potential leakages in profitability.
In the quadrant diagram below, these two variables are used to illustrate the space that many automotive suppliers play in.
Figure 1 - Risk Quadrant
Along the X-axis, the spectrum of unique customer requirements is represented. On the left side, the quote has no provisions to express unique customer requirements. On the right side, the quotation is primarily based on customer requirements.
On the vertical axis, the nature of production is shown. On the lower portion, production is for a single unit order. On the upper hand, the production volume is significant and can occur over an extended period … such as years.
Arcing from the top left quadrant to the lower right, are the various “build to n” manufacturing strategies. On one end of the spectrum, the order process for a build-to-stock (BTS) strategy is uneventful and binary. This strategy represents such consumer industry groups as packaged food products, electronics and appliances. The risks tend to be tied to seasonal trends, sales forecast and macro-economic considerations.
The arc continues with build-to-assemble (ATO), configure-to-order (CTO), build-to-order (BTO) and finally engineer-to-order (ETO). The quote for an ETO business will demand the resources of several disciplines and will typically require multiple quote submittals that can span months.
Many automotive suppliers (exempting tooling and manufacturing equipment suppliers) are a unique hybrid of strategies in that they produce quotations like an ETO business, but eventually enter production like a BTS manufacturer. Hence, the positioning of suppliers in the top right quadrant.
Automotive Supplier Lifecycle of Activities and Associated Data
Unlike most manufactures, automotive suppliers operate with the overarching framework of Advanced Product Quality Planning (APQP) procedures and techniques. The diagram below incorporates these procedures and highlights the primary lifecycle of activities.
Figure 2 - Automotive Supplier Lifecycle of Activities
The process starts with a quote, and proceeds into planning, design, validation, execution and finally support. Throughout these activities, dozens of various documents, procedures, calculations, plans, and checklists are produced. Here is a short list:
- design and process failure mode and effects analysis (D/PFMEA)
- engineering drawings
- engineering specifications
- gages/testing equipment requirements
- measurement systems analysis plan
- new equipment, tooling and facilities requirements
- packaging specifications
- production control plan
- reliability & quality goals
Invariably, this content is saved across the enterprise, ranging from individual computers, shared file folders, and perhaps cloud-based repositories.
To further drill into the various components of data represented in the above content, the figure below illustrates the numerous data items and their relationships.
Figure 3 - Data Items and Relationships
In generic terms, three primary data types are represented: program, product and manufacturing data.
For a program, the data/content types will typically include the quote, P&L, planning documents, schedules along with other data types. Also, there is likely a host of metadata attributes.
The product is described by specifications, calculations, CAD drawings and perhaps even electronic design automation (EDA) file types, along with quality, assembly instructions and so on.
Of course, once the program moves into productions, there are other data types that include schedules, tooling information, FMEA worksheets, manufacturing processes, approved vendors, etc.
Most of this data is disconnected from each other. Compounding the challenge is the fact that the processes inherently produce multiple versions with evolving data that is being added, edited and removed.
Elements Contributing to Risks
When putting the various data types and lifecycle activities together as portrayed above, the resulting operational challenges that unfold can be distilled to three key factors …
- disconnected data and their associated applications
- manual lifecycle processes
- lack of real-time visibility
Data is the product or the output of the various lifecycle activities. As a program evolves, the data grows in complexity and range of relationships. The applications that originate this data can include project management tools, configurators, CAD systems, ERP and customized spreadsheets. Also, extensive arrays of associated metadata exist. This can include file folder path names, labeled worksheets inside spreadsheet and email folders. Most of this data, associated applications and repositories are disconnected and would require a significant effort to follow relationships such as where-used and/or composed-of.
Although APQP practices are well established, suppliers also have the challenge of responding to additional requirements imposed by the OEM. These processes rely on decades of the experiences of team members and are facilitated by unstructured methods such as emails, telephone calls, and hall way discussions.
The figure below illustrates the relationship between the two factors of data cohesion and process repeatability.
Figure 4 - Data Cohesion and Process Repeatability Quadrant
On the horizontal axis, the spectrum represents disconnected data on the left and a single source paradigm on the right. The vertical axis represents the degree to which processes can be repeated consistently and reliably. On the lower end of the axis, processes are manual/verbal. On the upper end of the axis shows that processes are highly automated, repeatable and not necessarily dependent on the knowledge and experience of individuals.
The reality is that many suppliers live in the bottom left-hand corner where they are dealing with the inefficiencies, lack of visibility and leaks in profitability. The promise of PLM is represented in the upper right-hand corner, where data is connected and processes are repeatable.
Given the disparity of data and manual processes, gaining real-time visibility can be challenging. Score cards like the profit and loss (P&L), program status schedules and other key-performance indicators (KPIs) can be resource-intensive to produce. As a result, decisions could be based on outdated and/or incomplete and inaccurate data.
So, what is a supplier to do? Enter PLM.
What does PLM Deliver?
CIMdata is an industry analyst organization that recently commented on the kind of challenges addressed above. They said, “Companies need platforms and technology that can fill the large process gaps by managing workflows and capturing data while connecting and coordinating existing data silos.”
They further assert, “Companies get stuck with their legacy systems and solutions, which in turn impairs their abilities to respond to these challenges.” This impairment might more bluntly be translated as leakages in profitability.
How can organizations respond? Of course, CIMdata is referring to leveraging product lifecycle management (PLM) solutions.
PLM facilitates the digital transformation needed to respond to the various elements of risk discussed above. It is the means to manage the data, processes, and people needed to design, build, and service your organization's products. This enterprise-wide strategy creates a "single source of truth" for product information, establishes repeatable processes and provides real-time visibility that ultimately reduces risk and helps to achieve quoted profitability.
PLM and specifically the Aras platform is a proven solution. Companies such as major OEMs, Lear, Magna, and Schaeffler have vetted and embraced the PLM platform offered by Aras.
Stay tuned for Part 2 of this 2 Part Series, scheduled for our April 11, 2017 newsletter.