Article
Development Approach Model for Automotive Headlights with
Mixed Delivery Methodologies over APQP Backbone
Costel-Ciprian Raicu
1,
*, George-Călin Seri¸tan
2
, Bogdan-Adrian Enache
2
and Marilena Stănculescu
3
Citation: Raicu, C.-C.; Seri¸tan, G.-C.;
Enache, B.-A.; St˘anculescu, M.
Development Approach Model for
Automotive Headlights with Mixed
Delivery Methodologies over APQP
Backbone. Appl. Sci. 2021, 11, 10581.
https://doi.org/10.3390/app112210581
Academic Editor: Arkadiusz Gola
Received: 1 October 2021
Accepted: 5 November 2021
Published: 10 November 2021
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4.0/).
1
Doctoral School of Electrical Engineering, University “Politehnica” of Bucharest, 060042 Bucharest, Romania
2
Department of Measurements, Electrical Equipment and Static Converters, University “Politehnica” of
Bucharest, 060042 Bucharest, Romania; george.seritan@upb.ro (G.-C.S.); bogdan.enache2207@upb.ro (B.-A.E.)
3
Department of Electrotechnics, University “Politehnica” of Bucharest, 060042 Bucharest, Romania;
marilena.stanculescu@upb.ro
* Correspondence: costel_ciprian.raicu@stud.electro.upb.ro
Abstract:
Headlights’ development for the automotive industry is gaining a lot of volatility due
to frequent changes in features, styling and design, hardware interfaces, and software upgrades
required by the OEM, supplier, or new trends in regulations. Standard development models based
on V-cycle compliant with CMMI are not responding with reactivity on constant changes. The article
proposes an approach based on mixed development strategies over the different core domains with
Lean, Scrum, Feature-Driven Development, and VDI to satisfy the APQP milestones, with a proposal
of a canvas-type model, the rapid delivery of headlights is portrayed. The efficiency and effectiveness
of the model are assessed based on the assumed number of changes for new high-end headlights,
based on experience and real cases. A delivery baseline LED-based Headlight development—planned
versus actual—chart is presented and explained.
Keywords: agile; APQP; headlights; LED; lean
1. Introduction
Vehicles and electronic control units continue to increase in complexity [
1
,
2
]; the
software is allowing the customer to demand new functionalities with higher frequency,
and the unpredictability environment forced suppliers towards flexible and value-driven
approaches like agile project management [
3
]. Software products with their given value
proposition and malleability open the opportunity to combine Agile with the Lean method-
ology for the software domain [
4
]. For software development, Lean is a fuzzy term,
especially in the context of Agile methodology, but used to enhance software development
processes and scale up Agile [
5
], more commonly known today as scaled agile framework
(SAFe). Manufacturing organizations are driven by world-class performance and the
switch towards global economies, the moving target of quality control and the process of
improvement with the never-ending scopes, steered them towards lean and agile adoption
for enterprise scope [
6
]. Enterprises are adopting lean to achieve and develop the value
stream for eliminating waste, time, and schedule along with agility which is used for
market knowledge to exploit profitable opportunities in a volatile marketplace [7].
Advanced Product Quality Planning (APQP) is used for standardized quality manage-
ment in the automotive industry [
8
–
10
], and contains a methodical approach to define and
establish the needed measures to ensure the customer expectations for a given developed
product; this way, the information can be deployed across the organization between projects
with standardized documents to reduce their number and manage the quality [
11
]. The
project planning phase provides the structure for quality and rapid agility of integrating
all documents needed according to APQP [
12
]. The ability for firm guidance and execu-
tion over project phases must provide the means for documentation, revision, planning
recovery, and vision [
13
]. Quality standards and project objectives are ensured over the
Appl. Sci. 2021, 11, 10581. https://doi.org/10.3390/app112210581 https://www.mdpi.com/journal/applsci
